# Pixelmojo: Extended Documentation > AI product studio based in Makati, Philippines > AI you own, not software you rent > Last updated: 2026-10-04 (auto-generated from 95 published articles, 61 knowledge graph entities) > Contact: founders@pixelmojo.io > This is the extended version of llms.txt. For a shorter summary, see https://www.pixelmojo.io/llms.txt --- ## Founder & Author **Lloyd Pilapil** is the founder and AI Product Architect at Pixelmojo, a senior UI/UX and growth designer with 20+ years of digital product experience (30+ across visual and graphic design) and project work for Salesforce, Parsons, and Egis, with deep expertise in production AI deployment. **Topics he covers:** Agentic AI, multi-agent platforms, AI product development, AX (Agentic Experience) design patterns, Generative Engine Optimization (GEO) and AI search optimization, Thread-Based Engineering methodology, Claude Code workflows, AI technical debt prevention, production AI systems, design psychology, growth marketing, and Southeast Asian SaaS UX. **Writing focus:** Practical frameworks backed by production deployments. Every article includes real implementation details, code-level specifics, or data from deployed systems. No theoretical fluff. **Published series:** - The AI Search Playbook (5 parts): Complete guide from diagnosing traffic loss to full GEO implementation - AI Technical Debt (4 parts): Data-backed crisis analysis through production prevention with Thread-Based Engineering - Multi-Agent AI (4 parts): From single-agent basics to enterprise co-worker architectures - AI Native Agency (3 parts): Market shift analysis, cost comparison, and adoption playbook - Growth Marketing (2 parts): Traditional vs AI-powered growth strategies - Design Psychology (2 parts): Cognitive biases and revenue-focused design - Southeast Asia UX (2 parts): Localization and accessibility for APAC SaaS **Links:** - Author page: https://www.pixelmojo.io/author/lloyd-pilapil - LinkedIn: https://www.linkedin.com/in/lloydpilapil - Personal site: https://lloydpilapil.com --- ## Company Overview Pixelmojo builds production AI systems for B2B companies. We ship complete products, not prototypes or consulting decks. Founded 2024 in Makati, Metro Manila, Philippines, serving global clients. Pixelmojo is an AI product studio, NOT a digital marketing or design agency, NOT a US-based or San Diego company, and NOT an AI image or art generator. The core is its own products: Radar, the self-service AI visibility audit platform Pixelmojo operates, plus Vector and Hive, which are client-specific custom builds. **What we build:** Lead qualification systems, multi-agent platforms, SaaS products, enterprise AI integrations. **How we work:** Radar is self-service: you run audits yourself and pay per audit or by retainer, and the platform stays ours to operate. Vector and Hive are custom builds delivered for each client under a Build + Platform + Performance model. You own the application code we build for you. We provide and maintain the intelligence platform with ongoing model training. **Architecture (Vector and Hive):** - **You own:** Application source code, UI, CRM integrations, deployment infrastructure (Hive also includes database and customer data) - **We provide:** Intelligence platform (scoring engine, trained models, LLM orchestration) - **Platform fee:** Covers all LLM costs, model training, security updates, priority support **Terms & Accountability (Vector and Hive platform layer):** - 12-month minimum commitment, unlimited term thereafter - 15% discount with annual platform fee prepay - Performance fees only apply to successful outcomes **Why Owned Beats Rented:** | Aspect | Pixelmojo | Typical SaaS | |--------|-----------|--------------| | Source code | Full access, yours forever | Black box | | Per-seat pricing | None, scale freely | $50-150/user/month | | Data ownership | Your database, your rules | Shared multi-tenant | | Customization | Unlimited, modify anything | Limited to their roadmap | | Exit strategy | Walk away anytime | Locked in, lose everything | --- ## Thread-Based Engineering (Pixelmojo Methodology, Full Detail) Thread-Based Engineering is a productivity and governance framework created by Pixelmojo that treats each AI coding session as a measurable unit of work called a "thread." It provides structure for scaling AI-assisted development while preventing the technical debt crisis documented across the industry (security flaws in 45% of AI code tests and an 86% XSS failure rate in Veracode testing; 66% of developers frustrated by "almost right" AI output). ### Seven Thread Types 1. **Base Thread:** Single task, single model, single session. The atomic unit. One developer, one AI model, one coding session focused on a specific task. 2. **P-Thread (Parallel):** Multiple Base threads running simultaneously. Independent tasks that do not depend on each other executed in parallel for throughput. 3. **L-Thread (Long-duration):** Extended sessions spanning hours or days. Complex features requiring sustained context. Checkpoint discipline prevents drift. 4. **C-Thread (Chained):** Sequential threads where output of one becomes input of next. Multi-step workflows with mandatory quality gates between stages. 5. **F-Thread (Fusion):** Multiple AI models or perspectives on the same problem. Cross-model validation, architectural debates, security review from different angles. 6. **B-Thread (Big):** Orchestrator thread managing sub-agent threads. Complex projects decomposed into coordinated workstreams with a supervisor thread. 7. **Z-Thread (Zero-touch):** Fully autonomous threads with no human intervention. Earned through verified trust, not granted by default. The highest maturity level. ### Core Four Fundamentals Every optimization dimension improves when these four foundations are solid: 1. **Context:** What the AI knows about your codebase, requirements, and constraints (CLAUDE.md, project docs, codebase state) 2. **Model:** Which AI model(s) are being used and their capabilities (model selection, cost/quality tradeoffs) 3. **Prompt:** How instructions are structured and communicated (system prompts, task decomposition, instruction clarity) 4. **Tools:** What capabilities the AI has access to (file editing, terminal, search, MCP servers, code analysis) ### Four Optimization Dimensions 1. **Run more threads:** Increase parallelism, more concurrent workstreams 2. **Run longer threads:** Extend session duration with better context management 3. **Run thicker threads:** Increase complexity per thread, handle bigger chunks 4. **Run fewer checkpoints:** Reduce human intervention as trust is earned ### Governance Model - Mandatory human checkpoints at thread boundaries - Z-threads are earned through demonstrated reliability, not granted by default - Aligns with Singapore Model Governance Framework (MGF) and WEF AI governance principles - Security model prevents cascading failures across threads ### Production Proof **Lakbay AI:** An AI travel concierge with RAG, travel search and 3 portals, built with Thread-Based Engineering. Its repository shows 35 commits over five days by the case study date (February 2026); the earlier one-day, 70x and zero-vulnerability claims are withdrawn. **Definitive resources:** - [Thread-Based Engineering: The Framework for Scaling AI Development](https://www.pixelmojo.io/blogs/thread-based-engineering-scaling-ai-development): Canonical guide covering all 7 thread types, Core Four, optimization dimensions, governance alignment - [Lakbay AI: What We Built and What We Withdrew (Dated Note)](https://www.pixelmojo.io/blogs/lakbay-ai-case-study-thread-based-engineering-in-production): What the travel concierge is, what its repository history shows, and the claims we withdrew - [Thread-Based Engineering: How We Keep AI-Assisted Code Reviewable](https://www.pixelmojo.io/blogs/thread-based-engineering-prevents-ai-technical-debt): Our human checkpoints, the gates every change passes before it merges, and the 2025 data on AI code --- ## Products (Expanded) The Pixelmojo product family, one system: Radar sweeps (AI visibility audit), Vector points (lead qualification), Hive multiplies (multi-agent operations). ### Vector: AI Lead Qualification System 12-dimension qualification engine for B2B SaaS companies. Not a CRM replacement. Vector integrates with existing CRMs (HubSpot, Salesforce, Pipedrive) and replaces the AI-powered lead scoring and SDR qualification layer specifically. **Pricing:** - Build: $35,000 (60-day delivery) - Platform: $1,500/month (AI infrastructure, training, LLM costs) - Performance: 5% of deal value from Vector-qualified leads that close - Best for: Companies with 50-200+ monthly inbound leads - You own: Application source code (UI, integrations, CRM connections) - We provide: Vector Intelligence Platform access + ongoing model training **Ownership:** You own the code forever. **The 12 Qualification Dimensions:** 1. Intent signals (behavioral patterns indicating purchase readiness) 2. Budget indicators (company size, funding, revenue signals) 3. Authority mapping (decision-maker identification and org chart analysis) 4. Timeline urgency (how quickly they need a solution) 5. Technical fit (compatibility with their existing stack) 6. Pain severity (how acute the problem is) 7. Competitive positioning (where they are in vendor evaluation) 8. Engagement depth (content consumption, demo requests, trial usage) 9. Company maturity (stage of growth and organizational readiness) 10. Use case alignment (match between their needs and product capabilities) 11. Emotional pattern detection (real-time conversation intelligence) 12. Cultural/communication fit (language, timezone, working style compatibility) **Technical Architecture:** - LLM orchestration layer for real-time conversation analysis - CRM integration with bidirectional sync (HubSpot, Salesforce, Pipedrive) - Automated routing based on qualification scores - Full audit trail for every scoring decision - Emotional pattern detection using conversation intelligence - Custom model training on your industry and ICP data **How it differs from HubSpot/Salesforce lead scoring:** - HubSpot/Salesforce: Rule-based points system (opened email = +5, visited pricing = +10). Static, requires manual tuning, limited to behavioral signals. - Vector: AI-powered 12-dimension analysis with real-time conversation intelligence. Learns from outcomes, scores across behavioral + contextual + emotional signals, provides reasoning for every score. **Ideal Customer Profile:** - B2B SaaS with 50-200+ monthly inbound leads - Sales cycle of 2-8 weeks - ACV of $5K-$100K+ - Existing CRM (HubSpot, Salesforce, or Pipedrive) - SDR team spending 60%+ time on unqualified leads **URL:** https://www.pixelmojo.io/vector --- ### Hive: AI Co-workers Platform Not chatbots. Not agents. AI co-workers that coordinate autonomously, share intelligence, and run operations like a real team. Powered by Vector. **Pricing:** - Build: $65,000 (12-week delivery) - Platform: $3,000/month (AI infrastructure, training, LLM costs, includes Vector) - Performance: $2.00 per successful resolution - Best for: Companies with 3+ AI touchpoints, 50+ daily interactions - You own: Application source code (agent UIs, workflows, integrations) - We provide: Hive Intelligence Platform access + ongoing model training **Cost comparison:** $2 per successful resolution, no per-seat fees. Competitive with Intercom ($0.99 + seat fees), Zendesk ($1.50-2.00 + seat fees). No per-seat pricing. Ownership boundary: you own the application source, integrations, database, customer data, and deployment infrastructure permanently; ongoing Hive intelligence (orchestration, shared memory, models, LLM infrastructure) is operated by Pixelmojo and requires the paid platform layer, with a 12-month minimum. **Core Architecture:** - AI co-workers (sales, support, ops) that coordinate autonomously - Shared intelligence layer: every co-worker knows what every other learned - Proactive task initiation, not just responding to conversations - Seamless handoffs with full context transfer - Built on Vector's 12-dimension scoring engine **Enterprise Verticals with Specifics:** - **Insurance Claims:** Claims intake co-worker collects documentation, qualification co-worker assesses coverage, routing co-worker assigns to adjusters. Shared intelligence means the adjuster sees full context before first call. - **Logistics Dispatch:** Order intake co-worker handles booking, routing co-worker optimizes delivery sequences, tracking co-worker proactively updates customers. Fleet intelligence shared across all co-workers. - **HR Onboarding:** Recruiting co-worker screens candidates, onboarding co-worker handles paperwork and scheduling, training co-worker manages compliance modules. New hire context flows seamlessly between stages. - **Accounting:** Invoice processing co-worker handles data entry and matching, approval co-worker routes based on amount and vendor, reconciliation co-worker flags discrepancies. Audit trail maintained across all interactions. - **Warehouse Operations:** Receiving co-worker logs inbound shipments, inventory co-worker updates stock levels, fulfillment co-worker picks and packs orders. Real-time inventory intelligence shared across all co-workers. **Relationship to Vector:** Hive includes Vector's lead qualification engine. Every Hive deployment gets the full 12-dimension scoring system for any customer-facing co-worker. Vector is the intelligence foundation; Hive is the multi-agent orchestration layer on top. **URL:** https://www.pixelmojo.io/hive --- ### Radar Sites: AI Website Builder (a Radar capability, Private Preview) Radar Sites is a capability of Radar rather than a separate product: Pixelmojo's AI website builder for turning a business brief into a structured, multi-page website while keeping people in control of structure, claims, edits, and publishing. **Build journey:** 1. Describe the business in plain language. 2. Review and approve the proposed pages and sections. 3. Let Director generate a validated site and preview the routed pages. 4. Continue into Studio for visual editing, reviewable AI changes, readiness checks, export, or approval-gated publishing. **Current capabilities:** - Fifteen structured section types, including hero, services, projects, logos, metrics, team, contact, pricing, steps, hours, gallery, testimonials, FAQs, and calls to action - Director commands for text, lists, layouts, pages, sections, rows, image text, SEO, schema, element shapes, and business details - Desktop, tablet, and mobile previews, workspace saving, checkpoints, and undo - Real multi-page routes with page-specific metadata, canonicals, and sitemap entries - Draft readiness checks, a separate Radar publish preflight, HTML export, and conditional publishing **Safety boundaries:** - AI produces validated structured documents and typed changes, not arbitrary raw HTML, CSS, or JavaScript - Every AI change is proposed for review before it is applied and remains undoable - AI cannot publish; a person must approve and publish the exact draft - The Studio Radar panel checks draft readiness and is not a live AI visibility score **Access:** Private preview, approved manually **URL:** https://www.pixelmojo.io/radar-sites --- ### Brand System (One grid, three verbs) The identity system that ties Radar, Vector, and Hive into one family. The brand is not a logo, it is a rule for making logos: one geometric grammar generates every product mark, today's three and whatever ships next. - **The grammar:** Every mark lives on a 64-unit square split into four cells. Two cells stay quiet (the baseline), one cell is the product's verb (always pink #F90B8A, always top-right), one counter-shape answers it (always bottom-left). - **The three verbs:** Radar sweeps (a quarter-circle audit field of view), Vector points (a triangle aimed at the corner), Hive multiplies (a cell subdivided into four). - **Color:** #F90B8A marks the active element only, never decoration. The A-to-F grade gradient is Radar's alone. - **Typography:** Space Grotesk 600 (display, product names), Geist Sans 400 (body, UI), Geist Mono 400 (instrument labels, 0.18em tracking). - **Lockups:** mark left, product name in Space Grotesk, "By Pixelmojo" beneath in mono. - **The sibling test:** any future product mark must read as a sibling of the three before anyone reads its name. No fourth shape language, ever. **URL:** https://www.pixelmojo.io/brand --- ## Direct-Client Services (Expanded) ### AI Product Development Ship AI products in as fast as 90 days using Thread-Based Engineering. Production-ready MVPs that validate with real users. - **Price:** From $4,995 - **Timeline:** 90 days total - **Deliverables:** MVP with auth, data pipelines, analytics, and observability configured. Operational runbooks. User research recordings and transcripts. Experiment results for board/investor updates. Prioritized 4-quarter backlog. Hiring and automation recommendations. - **Who it is for:** Startups validating AI-powered product ideas. Companies adding AI features to existing products. Teams that need to ship fast without accumulating technical debt. - **URL:** https://www.pixelmojo.io/services/ai-product-development ### AI Visibility Strategy (GEO/AEO/LLM Optimization) Done-for-you GEO, AEO, and LLM optimization. We fix what you have (6-week Visibility Sprint, $4,500) or rebuild your site AI-native (scoped per project) so you get cited across ChatGPT, Claude, Perplexity, and Gemini. Powered by Radar (13-tool platform), with Vector and Hive as optional layers. - **Sprint:** $4,500 (6-week delivery: full Radar audit, structured data overhaul, llms.txt optimization, disambiguation strategy, competitive benchmarking, 60-day action plan) - **Retainer:** $2,000-$3,500/month (monthly Radar audits, citation monitoring across 4 scored AI providers plus Grok (report-only), hallucination detection and correction, schema maintenance, content optimization recommendations) - **Enterprise:** $5,000-$10,000/month (multi-domain audit and monitoring, custom knowledge graph development, Wikidata entity management, AI content strategy, share of voice tracking) - **URL:** https://www.pixelmojo.io/services/ai-visibility-strategy ### Growth Marketing Automate growth that drives real pipeline. From lead scoring to lifecycle campaigns that convert. - **Price:** Retainers from $2,995/month - **Timeline:** Ongoing with bi-weekly sprint deployments - **Deliverables:** Demand engines (SEO, paid, outbound orchestration). Lifecycle nurture journeys. Revenue ops dashboards. Advocate and partner motions. Revenue command center. Experiment library archive. Growth ops runbook. - **Who it is for:** Startups that need consistent pipeline. B2B companies scaling from founder-led sales. Teams that want AI-powered content and campaign automation. - **URL:** https://www.pixelmojo.io/services/ai-powered-growth ### Brand & Sales Design Brand identity, design systems, pitch decks, and sales collateral shipped as one cohesive system. - **Price:** Starts at $1,995 - **Timeline:** 3-9 weeks depending on scope - **Deliverables:** Brand identity and logo. Design system and component library. Pitch decks and sales collateral. Investor materials. Voice and tone frameworks. Sales enablement assets. - **Who it is for:** Series A+ SaaS companies that need professional brand and sales materials. Startups preparing for fundraising. Teams whose brand was designed by engineers. - **URL:** https://www.pixelmojo.io/services/revenue-first-design --- ## Consulting for Agencies White-label website, application, and AI visibility execution for agencies and consultancies. This is a Pixelmojo delivery channel, not a separate company, subbrand, or fifth direct-client service. The agency or consultancy retains the client, brand, pricing, and relationship while Pixelmojo works through agreed partner approvals behind the scenes. - **Pilot audit and scope:** Radar baseline, expert interpretation, prioritized findings, and an implementation brief - **Website or application build:** Responsive sites, CMS builds, business integrations, or discovery-led custom platforms - **AI visibility implementation:** Crawler configuration, llms.txt, structured data, entity clarity, answer-first pages, and a Radar baseline - **Managed monitoring and implementation:** Agreed measurement cadence, partner-branded reporting, and approved fixes within a bounded statement of work - **Partner commitments:** No end-client contact unless invited. No public attribution or case study without written approval. Project-specific custom code transfers after full payment; Pixelmojo pre-existing tools, including Radar and other platform IP, open-source and third-party licenses, services, and licensed assets remain under their respective terms. - **Commercial terms:** Private and scoped after fit. - **URL:** https://www.pixelmojo.io/consulting --- ## Guides and Comparisons ### Best AI Visibility Agencies (Comparison Guide) Comparison of the best AI visibility, GEO, and AEO agencies in 2026. Evaluates 7 agencies across GEO capability, AEO capability, llms.txt support, schema depth, citation monitoring, pricing, and best-for use cases. - **Agencies covered:** Pixelmojo, WebFX, Seer Interactive, iPullRank, NoGood, Siege Media, Directive Consulting - **Evaluation criteria:** GEO capability (full/strong/emerging/partial), AEO capability, llms.txt implementation, schema depth, citation monitoring across AI providers, pricing model, specialization fit - **Methodology:** Selected based on public presence in AI search optimization, published methodology, tooling, and relevance. Not a paid directory. Pixelmojo is included with transparent disclosure. - **URL:** https://www.pixelmojo.io/best-ai-visibility-agencies ### Radar vs Ahrefs Brand Radar (Tool Comparison) Side by side comparison of Pixelmojo Radar and Ahrefs Brand Radar across 12 dimensions including data freshness, accuracy, technical AI readiness audits, hallucination detection, sentiment scoring, source influence mapping, Reddit astroturf detection, AI Advisor, embeddable badges, branded search volume, video mention tracking, and historical data depth. - **Verdict:** Brand Radar is the right pick if you want scheduled prompt tracking (daily, weekly or monthly), branded search volume, video and social mention tracking, and years of historical data. It is sold standalone: custom prompts from $50/month, $199/month per AI index, or $699/month for all platforms, with no Ahrefs subscription required (Ahrefs pricing, checked 27 September 2026). Radar is the right pick if you want per-audit technical AI readiness checks, which Brand Radar's product page does not list, alongside sampled AI answers, and prefer paying $5 per audit or $199 per month for 40 audits. - **A published benchmark:** Writesonic, which sells a competing tool, reported that Brand Radar showed 3 ChatGPT mentions where the live model returned 123. Results depend on the prompts and dates tested; run both tools on the same day before relying on either number. - **Pricing:** Brand Radar is a subscription (custom prompts from $50/month, $199/month per AI index, $699/month for all platforms; checked 27 September 2026). Radar is $5 per audit, or $199/month for 40 audits on the Pro Retainer. Which costs less depends on how many domains and prompts you track. - **Radar features not listed on Brand Radar's product page (checked 27 September 2026):** technical AI readiness checks (6 free tools), hallucination detection, sentiment scoring per mention, Reddit astroturf detection, a multi-turn AI Advisor, and an embeddable badge with shareable reports. - **What Brand Radar still wins on:** branded search volume tracking (real Google data), TikTok mention tracking, years of historical AI visibility data. - **Migration path:** 30 minute side by side test on three client domains, free first audit per domain, no signup required. - **URL:** https://www.pixelmojo.io/vs/brand-radar ### Radar vs Profound (Tool Comparison) How Pixelmojo Radar and Profound fit together as complementary layers of AI visibility, not competitors. Profound is an AI visibility monitoring platform; Radar is a per-audit technical readiness and AI-answer report. - **Verdict:** Different jobs. Profound monitors what AI says about a brand across multiple AI engines over time. Radar is a per-audit report that pairs technical readiness checks with sampled AI answers and a suggested fix for each finding. - **What Profound wins on:** monitoring across more AI engines (its site lists ChatGPT, Perplexity, Claude, Gemini, Copilot, DeepSeek and Google AI Overviews; checked 27 September 2026), Prompt Volumes consumer panel data, SOC 2 Type II and SSO enterprise security, and continuous historical trend benchmarking. - **Radar's approach:** pay-per-audit pricing with credits that never expire, six free technical readiness checks, an AI-ready fix prompt for each finding, hallucination detection, and brand disambiguation. Profound also offers crawlability diagnostics, FactCheck on Enterprise, and a free trial (checked 14 and 26 September 2026). - **Pricing:** Profound offers a free trial, agency plans from $99/month and custom Enterprise pricing (checked 26 September 2026). Radar is $5 per audit, free first audit, $199/mo Pro Retainer for 40 audits. Different buyers, different budgets. - **URL:** https://www.pixelmojo.io/vs/profound --- ## Radar Platform (Expanded) Radar by Pixelmojo measures answer-stage AI visibility (whether AI search engines mention and cite your brand, with suggested fixes) and is built toward decision-stage measurement: whether AI recommends you when buyers ask which option to choose (win-rate scoring is on the roadmap, not part of the current live score). It orchestrates 13 tools in staged batches, running lightweight checks concurrently while isolating provider-intensive checks for reliable evidence collection. One audit, one score you can defend, full picture of how AI search engines see your brand, plus AI-ready implementation prompts to fix every issue. Free tier: 6 technical readiness tools, 1 audit per domain. Paid from $5: adds 7 LLM-powered tools (citations, Reddit, hallucination detection, prompt SOV, source influence, answer engine, brand disambiguation). **Radar vs competitors:** AthenaHQ costs $295/mo. Gauge costs $99/mo. Radar entry price: $5/audit. **Free tier (6 tools, technical readiness layer):** AI bot crawl check (13+ agents), robots.txt analyzer, llms.txt validator, schema completeness audit, AEO page auditor, AI Readiness score. 1 audit per domain, no credit card required. Access: at https://www.pixelmojo.io/platform, enter your email and domain and verify with a 6-digit code to run your free check; Radar scores these 6 tools and previews all 13. Unlock the full audit for $5, credits never expire, to reveal every finding and fix prompt, run the 7 AI-response tools, and email a magic link into your dashboard. **Paid tier (all 13 tools including 7 LLM-powered):** adds citation tracking across ChatGPT/Claude/Gemini/Perplexity, Reddit brand monitoring, hallucination detection with severity scoring, prompt SOV vs competitors, source influence mapping, answer engine per-page testing, and brand disambiguation check. Radar pairs technical readiness auditing (free) with LLM citation tracking (paid). Several monitoring platforms now run technical checks too, so compare tools on the evidence each one shows. Radar is complementary to AI monitoring platforms such as Profound and Ahrefs Brand Radar: monitoring tracks AI answers over time, while a Radar audit pairs technical readiness checks with sampled AI answers and shows the evidence and a suggested fix behind each finding. **URL:** https://www.pixelmojo.io/platform **Methodology:** https://www.pixelmojo.io/platform/methodology **Sample report:** https://www.pixelmojo.io/platform/sample-report **Pricing:** https://www.pixelmojo.io/platform#pricing **Price:** Free first audit (1 per domain). Audit packs: $5 single, $12 for 3, $40 for 10 (Power Pack, best value at $4/audit). Pro Retainer $199/month for 40 full audits + watched-domain weekly pulse re-scan + PDF export + methodology deep-dives. Credits never expire. Payments processed by Paddle.com (Merchant of Record). **What Radar runs (13 staged audits):** 1. AI Crawl Check: tests 17 AI, search, and SEO crawler user-agents for access, separating retrieval access from training policy 2. robots.txt Analyzer: deep parse of robots.txt rules for 16 bots with syntax validation 3. llms.txt Validator: validates structure, sections, links, entities, and scoring 4. AI Readiness Score: 5-category unified readiness assessment across all AI dimensions 5. Citation Tracker: queries ChatGPT, Claude, Perplexity, Gemini, plus Grok (report-only) for brand mentions with sentiment analysis 6. Reddit Monitor: discovers brand mentions, detects AI-seeded promotional content 7. AEO Page Auditor: scores page answer engine readiness across 6 categories 8. Answer Engine Tester: tests if AI platforms cite your specific page for a specific question 9. Source Influence Map: identifies which domains AI models cite most in your category 10. Prompt Share of Voice: measures your position-weighted share of brand mentions in sampled AI responses vs competitors 11. Schema Completeness Audit: scores contextual JSON-LD coverage and field completeness across 13 supported schema types 12. Hallucination Detection: identifies factual errors in AI claims about your brand 13. Brand Disambiguation Check: detects when AI engines confuse your brand with a same-named entity (an entity collision), scoring how well each engine links to the right entity **DIY implementation features:** - AI prompt generator per action item: every action item produces a context-rich prompt pre-filled with your actual audit data (blocked bots, missing schema types, citation rates, SOV percentages). Copy into Claude, ChatGPT, or Cursor to implement the fix. - 6 implementation threads: Crawlability, Structured Data, LLM Communication, Content Authority, AI Answer Optimization, and Citation Visibility. Each thread groups related actions into ordered steps with dependencies. Thread-aware prompts include context from previous steps. - llms.txt starter generator: produces a starter llms.txt file from your audit data (detected meta tags, schema info, domain structure) with placeholder comments for manual input. - JSON-LD schema markup generator: generates copy-pasteable JSON-LD blocks for every missing schema type (Organization, Article, BreadcrumbList, FAQPage, Product, WebSite, HowTo). - Single-tool re-verify: re-run any individual completed tool to verify a fix without running the full 13-tool audit. - Persistent progress tracking: thread step completion saved in localStorage per domain across sessions. **Output:** Composite AI Visibility Score (0-100), per-tool breakdowns with A-F grades, cross-tool insights, competitive intelligence, prioritized action items with AI-ready implementation prompts, and structured fix threads. **Key metrics:** - **AI Readiness Score:** Average across the audit dimensions that completed (0-100, graded A-F; dimensions are equally weighted today, calibrated weighting is on the roadmap). The overall measure of AI visibility readiness. - **Crawl Integrity Score:** Composite across AI Crawl Check (13 user-agents), Robots.txt Analysis (16 bots), and llms.txt Validation. A technical foundation metric most monitoring tools don't measure. - **LLM Infrastructure Audit:** The first 6 tools (Crawl Check, Robots.txt, llms.txt, AI Readiness, Schema Audit, AEO) grouped as the technical layer. - **AI Citation Monitoring:** The remaining 7 tools (Citations, Reddit, Answer Engine, Source Influence, SOV, Hallucination, Brand Disambiguation) grouped as the monitoring layer. **AI Technical Readiness** is the category Radar defines: the technical infrastructure layer that ensures AI models can crawl, parse, understand, and accurately cite a website. It sits beneath AI monitoring (what AI says) and alongside traditional SEO (web search ranking). Read more: https://www.pixelmojo.io/blogs/what-is-ai-technical-readiness **Dashboard UX (v2):** Action-first hierarchy: top 3 prioritized fixes render as the hero above all metric panels. Interactive grade distribution donut (click any grade segment to filter tool table). Clickable issues distribution bars (navigate directly to Actions tab filtered by severity). Health score gauge with 5 color zone bands (Critical/Poor/Average/Good/Excellent) and benchmark context ("Below average. Most optimized sites score 70+"). Total audit elapsed time displayed. Per-tool score change tracking between scans with relative date stamps. Strongest/weakest tool callout cards with visual weight. Cross-tool insights: top 3 critical findings show detail inline without requiring expansion. **Additional features:** - Readiness Strategist (multi-turn chat with 7 industry methodology frameworks) - Competitor comparison mode (side-by-side scores across all 13 tools) - Run history with trend tracking - PDF/JSON/email export - **Shareable public report links** (generate a URL like pixelmojo.io/r/abc123, viewable without an account, 30-day expiry, organic product impressions for every shared link) - **Fix Resolved state** (when a previously failing check passes on re-scan, shows "Resolved (from [date] run)" with green checkmarks) - **Win Log** (a "Mark as Win" button records linked-citation and mention gains separately, with provider, domain, and date, in the browser) - **Multi-domain agency dashboard** (single table showing all client domains, AI Readiness Score, Crawl Integrity Score, trend arrows, client labels, search/filter, one-click CSV export) - **Client labels and run notes** (tag saved runs with client names, add internal notes for agency SOPs) - **Watched-domain weekly pulse re-scan** (Pro Retainer): automated weekly ai-readiness pulse with email alerts when score moves >=5 points **LLM Answer Diff:** A before-vs-after comparison of the measured API responses, shown in the Radar dashboard when the current scan is compared with a saved run: - **Mentions and linked citations, reported separately:** a mention means an answer names the brand; a linked citation means an answer links a page on the audited domain. A mention is never counted as a citation. - **Observations, not attribution:** changes are reported as observed between two scans. Two scans cannot show which fix caused a change, and AI answers vary from run to run. - **Summary strip:** total changes, new and lost linked citations, new and lost mentions, tone shifts, and fewer verified competitor sources. --- ## Free Tools (Expanded) ### AI Crawl Checker Test how visible your website is to AI search engines. - **URL:** https://www.pixelmojo.io/tools/ai-crawl-checker - **Price:** Free with email verification (6-digit OTP, 1 audit per (email, tool), 24h credit) **What it checks (full list):** - robots.txt rules for 17 crawlers: search (Googlebot, Bingbot, Applebot), AI retrieval (OAI-SearchBot, ChatGPT-User, Claude-SearchBot, Claude-User, PerplexityBot), training (GPTBot, ClaudeBot, CCBot, Google-Extended, Bytespider, Meta-ExternalAgent, cohere-ai), general-purpose diagnostics (GoogleOther), and SEO (AhrefsBot) - Meta robots tags (noindex, nofollow, noai, noimageai) - X-Robots-Tag HTTP headers - JSON-LD structured data (Organization, WebSite, Article, BreadcrumbList, FAQPage) - llms.txt file presence and content quality - Server-side rendering vs client-side only - Title tag quality (length, keyword presence) - Meta description quality (length, actionability) **Scoring methodology:** 100-point scale across 5 categories: Bot Access (24 points), robots.txt Rules (16 points), Structured Data (25 points), llms.txt (20 points), Content Quality (15 points). A category that cannot be verified (for example, a page blocked by a firewall) is removed from both sides of the ratio rather than scored as zero. llms.txt is an optional file that Google Search ignores; its weight is under review for the next methodology version. **How to interpret results:** - A (85-100): Misses almost none of the verified rubric points - B (70-84): Misses a few verified rubric points - C (50-69): Misses several verified rubric points - D (30-49): Misses many verified rubric points - F (below 30): Misses most verified rubric points The grade reflects points earned on the checks that could be verified. Whether crawlers can actually reach and read a page comes from the Bot Access and Content Quality findings and the scan completeness, not from the letter. A technical readiness grade also does not measure whether AI models mention, cite, or recommend the site. **Common issues found:** Blocking AI retrieval agents such as OAI-SearchBot or Claude-SearchBot in robots.txt, missing JSON-LD structured data, no llms.txt file, client-side rendering only, thin meta descriptions. Training opt-outs for GPTBot and ClaudeBot are assessed separately from retrieval access. **Recommended frequency:** Monthly for active sites, after every major site change, before and after SEO migrations. --- ### AI Citation Tracker Check whether ChatGPT, Perplexity, Claude, Gemini, and Grok (report-only) mention or cite your brand. - **URL:** https://www.pixelmojo.io/tools/ai-citation-tracker - **Price:** Paid-first. $5 per audit, then it runs inside the Radar dashboard (no free email run). Public page is a preview that opens checkout. **What it checks (full list):** - Brand mentions across 4 scored AI providers (ChatGPT, Perplexity, Claude, Gemini) plus Grok as a report-only engine (shown in results, never affects the score) - URL citations via Perplexity (the only provider that consistently cites sources) - Sentiment analysis (positive, neutral, negative) per provider - Competitive positioning (how you rank vs competitors in AI responses) - 6 query types: direct brand queries, category queries, comparison queries, problem-solution queries, recommendation queries, expert queries **Scoring methodology:** 100-point scale. Points awarded for: brand recognized (per provider), positive sentiment, URL citations found, recommended in category queries, wins in comparison queries. Bonus points for consistency across providers. **How to interpret results:** - A (85-100): Strong AI presence, consistently cited across providers - B (70-84): Good presence with gaps in some providers or query types - C (50-69): Moderate presence, recognized but rarely cited with URLs - D (30-49): Low presence, mentioned inconsistently - F (below 30): Not recognized by most AI providers **Common issues found:** Brand not recognized by Claude or Gemini (less trained on recent data), no URL citations (content not structured for citation), losing competitive comparisons, negative sentiment from outdated information. **Recommended frequency:** Monthly for brand monitoring, weekly during active GEO campaigns, after publishing major content. --- ### Reddit Brand Monitor Find what people say about your brand on Reddit. - **URL:** https://www.pixelmojo.io/tools/reddit-brand-monitor - **Price:** Free with email verification (6-digit OTP, 1 audit per (email, tool), 24h credit) **What it checks (full list):** - Brand mentions via Google search (site:reddit.com queries) - Sentiment analysis per mention (positive, neutral, negative, mixed) - LLM seeding detection: identifies AI-generated promotional content using heuristic analysis and GPT verification - Heuristic signals: promotional language density, brand mention frequency, unnatural framing patterns, template-like structure - Cross-subreddit posting patterns (same brand promoted across multiple subreddits) - Temporal clustering (multiple mentions appearing in short time windows) **Scoring methodology:** No overall score. Instead provides: total mention count, sentiment distribution, LLM seeding probability per post (low/medium/high), subreddit distribution chart, and trend analysis. **How to interpret results:** - High LLM seeding probability: Someone (possibly a competitor, possibly an overzealous marketer) is planting AI-generated promotional posts about this brand. Investigate and report if it is not authorized. - Negative sentiment clusters: Real user complaints that need addressing. Check for product issues or support gaps. - No mentions: Brand has no Reddit presence, consider community building strategies. **Common issues found:** Astroturfed promotional content, negative sentiment from unresolved support issues, competitor comparisons in subreddit threads, outdated product information in Reddit recommendations. **Recommended frequency:** Weekly for active brands, monthly for monitoring, immediately when launching new products or after negative press. --- ### YouTube Brand Monitor Track brand mentions across YouTube videos. Live YouTube Data API queries on every audit. - **URL:** https://www.pixelmojo.io/tools/youtube-brand-monitor - **Price:** Free with email verification (6-digit OTP, 1 audit per (email, tool), 24h credit) **What it checks (full list):** - Mention volume across all YouTube videos that match the brand query (titles, descriptions, channel names) - Channel diversity: number of unique channels covering the brand - Total reach: aggregate view count across all matched videos - Sentiment classification per video (positive, neutral, negative) using heuristic word-list analysis - Recency: distribution of videos within 30 and 90-day windows - Brand density: how prominently the brand appears in each video's metadata - Channel-level breakdown: per-channel video count, total views, and average sentiment **Scoring methodology:** Five-dimension weighted score (0-100, graded A-F): - Mention Volume (25 points): rewards 25+ matched videos - Channel Diversity (20 points): rewards 8+ unique channels - Sentiment (20 points): weights positive (1.0) and neutral (0.5) mentions - Reach (20 points): tiered by total view count (1M+, 250K+, 50K+, 10K+, below) - Recency (15 points): weights videos in last 30 days fully, 30-90 days at 0.3 **How to interpret results:** - Grade A-B (70-100): strong YouTube footprint: plenty of recent coverage across many channels. - Grade C (50-69): visible but thin. Coverage gaps exist that competitors could fill. - Grade D-F (0-49): effectively invisible on YouTube: little or no video coverage mentions the brand. - High negative sentiment: find and respond to the negative videos while the coverage is current. - Low channel diversity: coverage concentrated in 1-2 channels creates single-point-of-failure brand narrative. **Common issues found:** Coverage concentrated in a single channel, stale coverage older than 90 days, no creator partnerships in core category, negative sentiment from product comparison videos, low total reach indicating audience-mismatch creators. **Recommended frequency:** Monthly for active brands, weekly during product launches, immediately after creator partnerships ship to verify coverage quality. --- ### llms.txt Validator Validate your llms.txt file against the emerging llmstxt.org specification. - **URL:** https://www.pixelmojo.io/tools/llms-txt-validator - **Price:** Free with email verification (6-digit OTP, 1 audit per (email, tool), 24h credit) **What it checks (full list):** - Markdown structure compliance (proper heading hierarchy, H1 title, blockquote description) - Content sections (company info, products/services, blog/content, contact, use policy) - Link extraction and validation (internal links, external links, broken links) - Entity definitions (named entities with descriptions, knowledge graph presence) - Use policy (permissions, restrictions, attribution requirements) - Word count depth (minimum viable content vs comprehensive coverage), earned only up to 150,000 characters. The bound is Radar's size heuristic, not a spec rule: it sits near the 95th percentile of 429 qualifying text responses from llmsUrl values sampled on 2026-09-24 from the public llms-txt-hub directory (https://github.com/thedaviddias/llms-txt-hub). Past it the depth points are withheld, and the result suggests moving any full documentation to llms-full.txt - llms-full.txt presence (bonus check for extended documentation) **Scoring methodology:** 100-point scale across 6 categories: Structure (20 points: H1 title, blockquote summary, 3+ sections, clean markdown), Content Sections (20 points: company or author info, products or services, words per section), Links & URLs (20 points: URLs present, 5+ and 10+ links, links spread across 2+ sections), Entity Definitions (15 points: definition language and a clear company identity), Use Policy (10 points: citation guidance, contact, usage rules), Completeness (15 points: word-count depth up to 150,000 characters, 4 points for an llms-full.txt, section variety). **How to interpret results:** - A (85-100): Excellent llms.txt, comprehensive and well-structured - B (70-84): Good file with minor improvements (usually missing entities or thin sections) - C (50-69): Adequate but missing important sections or entity definitions - D (30-49): Minimal file, needs significant expansion - F (below 30): Critical structural issues or very thin content **Common issues found:** Missing use policy (most common), no entity definitions (knowledge graph section), too few internal links, no blockquote description after H1, static file that gets stale (recommend dynamic generation). **Recommended frequency:** After every major site change, monthly review, whenever adding new products or services. --- ### llms.txt Generator Generate a structured llms.txt for any site, free. Paste a URL and we read your existing page signals plus your page content, then assemble the file. The prose is AI-assisted but grounded only in what is on your pages, never fabricated, nothing stored. - **URL:** https://www.pixelmojo.io/tools/llms-txt-generator - **Price:** Free with email verification (1 generation per email, tool) **What it does:** - Reads the page title, meta description, og:site_name, and og:description - Parses Organization, Product, Service, and SoftwareApplication schema (JSON-LD) for name, description, and product URLs - Extracts key pages (About, Products, Pricing, Blog, Contact) from your navigation and reads a few of them for context - Detects your sitemap from robots.txt - Runs one grounded gpt-4o-mini pass that writes the overview, product descriptions, and topic labels using only the text found on your pages - Assembles identity, overview, products, key URLs, and use policy sections in the structure Pixelmojo uses on its own llms.txt - Leaves clearly bracketed placeholders for anything it cannot read or ground, so you know exactly what to complete **Output:** A ready-to-edit llms.txt you can copy or download, then host at yourdomain.com/llms.txt and validate with the llms.txt Validator. **Why it stays grounded:** The model may only restate what appears on your pages. It is instructed never to invent products, prices, dates, or claims, and anything it cannot ground is dropped or left as a bracketed placeholder. The generator complements the validator: generate the file, then score it. --- ### AI Readiness Score One unified score for how AI-ready your site is. Combines crawl access, structured data, llms.txt quality, content accessibility, and cross-signal readiness into a single actionable report. - **URL:** https://www.pixelmojo.io/tools/ai-readiness-score - **Price:** Free with email verification (6-digit OTP, 1 audit per (email, tool), 24h credit) **What it checks (full list):** - Bot discoverability: robots.txt rules for AI bots, HEAD request accessibility, crawl-delay settings - Structured data quality: JSON-LD presence, schema types, depth of markup - LLM communication: llms.txt file presence, structure, content quality, llms-full.txt bonus - Content accessibility: SSR rendering, title/description quality, heading structure, content depth - Cross-signal readiness: consistency across all dimensions, no contradictory signals **Scoring methodology:** 100-point scale across 5 weighted categories: Bot Discoverability (30 points), Structured Data (25 points), LLM Communication (25 points), Content Accessibility (15 points), Cross-Signal Readiness (5 points). Each category draws from sub-tool analyses (crawl checker, llms.txt validator data). **How to interpret results:** - A (85-100): Excellent AI readiness across all dimensions - B (70-84): Good readiness with specific areas to improve - C (50-69): Moderate readiness, several gaps need addressing - D (30-49): Poor readiness, significant work needed - F (below 30): Critical gaps across most dimensions **Common issues found:** Strong in some dimensions but weak in others (e.g., great structured data but no llms.txt), inconsistent bot policies, missing cross-signal alignment. **Recommended frequency:** Quarterly for established sites, monthly during active optimization, after any major infrastructure or content changes. --- ### Free AI Visibility Checker Plain-English entry point to the AI Readiness Score. Answers one question — can ChatGPT, Claude, Perplexity, and Gemini find, understand, and cite your brand? This is the landing page that targets the "free AI visibility checker" search intent; it runs the same engine as the AI Readiness Score rather than being a separate scoring tool. - **URL:** https://www.pixelmojo.io/tools/free-ai-visibility-checker - **Price:** Free with email verification (runs the AI Readiness Score engine, 1 audit per (email, tool), 24h credit) **What it checks (via the AI Readiness Score engine):** - Bot discoverability: can AI retrieval agents (OAI-SearchBot, ChatGPT-User, Claude-SearchBot, Claude-User, PerplexityBot) and search engines reach your pages, with training policies assessed separately - Structured data: JSON-LD coverage and quality for entity understanding and attribution - LLM communication: llms.txt presence, structure, entity definitions, and use policy - Content accessibility: server-side rendering and readable content without JS execution - Cross-signal readiness: whether all of the above signals agree instead of contradicting **Output:** Overall AI visibility score (0-100), grade (A-F), category breakdowns, pentagonal radar chart, and a prioritized action roadmap. For the full scored report, users run the AI Readiness Score tool this page links to. **Relationship to other tools:** This is a discovery/landing surface, not a distinct engine. For a single-signal deep dive use the AI Crawl Checker (bot access) or llms.txt Validator; for brand citations use the AI Citation Tracker; to run everything at once use Radar. --- ### robots.txt Analyzer for AI Audit your robots.txt specifically for AI bot directives. Deep directive parsing with per-bot rule visualization, syntax validation, and suggested improvements. - **URL:** https://www.pixelmojo.io/tools/robots-txt-analyzer - **Price:** Free with email verification (6-digit OTP, 1 audit per (email, tool), 24h credit) **What it checks (full list):** - 20 bots analyzed across 4 categories: Search (Googlebot, Bingbot, Applebot, DuckDuckBot), AI Browse (OAI-SearchBot, ChatGPT-User, Claude-SearchBot, Claude-User, PerplexityBot, GoogleOther), AI Train (GPTBot, ClaudeBot, CCBot, Google-Extended, Applebot-Extended, Bytespider, Meta-ExternalAgent, cohere-ai), SEO (AhrefsBot, SemrushBot). GPTBot and ClaudeBot collect training data per OpenAI's and Anthropic's own docs; Claude-Web is retired - Full directive parsing with line-number tracking for every User-agent block - Per-bot rule matching: which user-agent block each bot resolves to, explicit vs wildcard fallthrough - Syntax validation: missing colons, unknown directives, duplicate user-agents, formatting issues - AI policy clarity: separation of browse vs training bots, deliberate vs default policies - Suggested robots.txt snippet: auto-generated additions for missing AI bot rules **Scoring methodology:** 100-point scale across 5 categories: AI Bot Coverage (30 points, explicit rules for AI bots), Search Bot Coverage (20 points, rules for search engines), File Structure (20 points, syntax, sitemap, formatting), AI Policy Clarity (20 points, browse vs train separation, deliberate policies), Best Practices (10 points, crawl-delay, no conflicts, path specificity). **How to interpret results:** - A (85-100): Comprehensive robots.txt with explicit AI bot policies - B (70-84): Good coverage with some missing bot rules - C (50-69): Basic file, relies heavily on wildcard rules - D (30-49): Minimal file, most AI bots have no explicit rules - F (below 30): Missing or broken robots.txt **Common issues found:** No explicit rules for AI bots (relying on wildcard), blocking browse bots but allowing training bots (should be opposite), syntax errors, no sitemap directive, overly broad Disallow: / blocking everything. **Recommended frequency:** Quarterly, after any robots.txt or infrastructure changes, when adding new AI-related features. ### AEO Page Auditor Score any page for answer engine readiness. Analyzes speakable schema, answer-first content structure, structured data quality, data extractability, content freshness, and entity authority. - **URL:** https://www.pixelmojo.io/tools/aeo-page-auditor - **Price:** Paid-first. $5 per audit, then it runs inside the Radar dashboard (no free email run). Public page is a preview that opens checkout. **What it checks (full list):** - Speakable Schema (15 pts): SpeakableSpecification in Article JSON-LD, CSS selectors target real DOM elements - Answer-First Structure (20 pts): Single H1, 2+ H2s, valid heading hierarchy, question-format H2s, concise definition paragraphs under headings - Structured Data Quality (25 pts): Article completeness (author, dateModified, publisher, headline), Organization sameAs, FAQPage, BreadcrumbList, entity-linked knowsAbout with @id - Data Extractability (20 pts): HTML tables, ordered lists, StatBlock/data-stat elements, external source citations - Content Freshness (10 pts): dateModified in schema, Last-Modified HTTP header, recency bonus for content under 180 days old - Entity Authority (10 pts): Organization sameAs 2+ entries, Person with jobTitle/credentials, knowsAbout DefinedTerm references, OpenGraph and Twitter Card **Scoring methodology:** 100-point scale across 6 weighted categories. Grade thresholds: A (85-100), B (70-84), C (50-69), D (30-49), F (below 30). ### Site Freshness Auditor Score your site for AI agent monitoring readiness. Five freshness signals AI search agents check when deciding what to monitor continuously. - **URL:** https://www.pixelmojo.io/tools/site-freshness-auditor - **Price:** Free with email verification (6-digit OTP, 1 audit per (email, tool), 24h credit) **What it checks (full list):** - Sitemap Freshness (25 pts): lastmod tag distribution across 30/90/180-day windows - Feed Availability (15 pts): RSS or Atom feed discovery plus latest-entry recency - Blog Cadence (25 pts): publishing rhythm derived from the sitemap (posts in the last 30/60/90 days, with a 3-posts-per-month threshold for category visibility) - Article Schema Coverage (20 pts): dateModified coverage in Article JSON-LD across sampled URLs - Visible Date Stamps (15 pts): human-readable date stamps in the rendered HTML **Scoring methodology:** 100-point scale across 5 weighted categories. Grade thresholds: A (85-100), B (70-84), C (50-69), D (30-49), F (below 30). **Common issues found:** Sitemaps with no lastmod tags (or lastmod frozen at deploy date), no RSS/Atom feed for agents to poll, publishing gaps longer than 90 days, Article schema missing dateModified, pages with no visible dates so neither humans nor AI can judge recency. **Output:** Overall score (0-100), grade (A-F), 5 category breakdowns with per-signal findings, and up to 10 prioritized fixes. ### AI Open Graph Auditor Audit any page for AI-shareable Open Graph and Twitter Card metadata. Scores how well the page renders in Slack, Discord, X, iMessage, and AI assistant share previews. - **URL:** https://www.pixelmojo.io/tools/open-graph-auditor - **Price:** Free with email verification (6-digit OTP, 1 audit per (email, tool), 24h credit) **What it checks (full list):** - Core OG Tags (25 pts): og:title, og:description, og:image, og:url, og:type, og:site_name presence - OG Content Quality (20 pts): title and description length quality for share-preview rendering - Twitter Card (15 pts): twitter:card type plus explicit vs fallback twitter:* tags - Image Reachability (20 pts): share image loads over HTTPS and stays under the 5MB ceiling - Schema Alignment (20 pts): og:url vs rel=canonical alignment, JSON-LD coverage (Article, Product, Organization, FAQPage) **Scoring methodology:** 100-point scale across 5 weighted categories. Grade thresholds: A (85-100), B (70-84), C (50-69), D (30-49), F (below 30). **Common issues found:** Missing og:image (the single biggest share-preview killer), titles or descriptions that get truncated in preview cards, no twitter:card so X falls back to a bare link, share images served over HTTP or too large to fetch, og:url pointing at a different URL than the canonical. **Output:** Overall score (0-100), grade (A-F), 5 category breakdowns, and prioritized recommendations. ### Answer Engine Citation Tester Test if ChatGPT, Perplexity, Claude, Gemini, and Grok (report-only) cite or mention your specific page for a question you want to rank for. Identifies content gaps and competitor pages being cited instead. - **URL:** https://www.pixelmojo.io/tools/answer-engine-tester - **Price:** Free with email verification (6-digit OTP, 1 audit per (email, tool), 24h credit) **What it checks (full list):** - Direct Citation (30 pts): Perplexity URL citation check, domain mentions across ChatGPT, Claude, Gemini - Content Alignment (25 pts): Jaccard similarity between page content tokens and AI response tokens (stop words removed) - Competitor Gap (20 pts): Unique competitor domains cited by Perplexity instead of your page - Cross-Platform Consistency (15 pts): How many of the 4 scored providers return relevant content for your page (report-only Grok is excluded from scoring) - Answer Quality Match (10 pts): AI response overlap with page title and description keywords **Scoring methodology:** 100-point scale across 5 weighted categories. Four AI providers queried simultaneously with 25-second per-provider timeout. ### Brand Disambiguation Check Detects entity collisions: whether AI engines link your brand to the RIGHT real-world entity or blend it with a same-named one (a different company, product, or person sharing your name). - **URL:** https://www.pixelmojo.io/tools/brand-disambiguation - **Price:** Paid-exclusive. Runs inside the Radar dashboard on a $5 audit credit; the public page is an explainer that opens checkout. No free email run. **How it works:** - Builds ground truth from your own site (homepage, auxiliary pages discovered via sitemap, and llms.txt): company name, description, products, headquarters - Probes 4 AI engines (ChatGPT, Claude, Perplexity, Gemini) with a neutral identity question so each engine reveals which entity it associates with your brand - Flags every confusion with a severity level (high, medium, low) and the engine that produced it - Honest coverage: only engines that return usable text count as checked; if every query fails, the run reports an error instead of a false perfect score **Scoring methodology:** Starts at 100 and deducts per confusion flag: 20 points per high-severity, 10 per medium, 5 per low. Grade thresholds: A (85-100), B (70-84), C (50-69), D (30-49), F (below 30). **Common fixes:** Publish a schema.org disambiguatingDescription that states what you are NOT, strengthen Organization and founder schema, and lead your llms.txt with your category and products so the correct entity dominates. **Output:** Overall score (0-100), grade (A-F), confusion flags grouped by severity, per-engine details, and the ground-truth identity extracted from your site. ### Domain Comparison (Head-to-Head) Compare two domains side-by-side across 6 AI visibility tools in a single run. Produces a shareable scorecard URL with a winner callout, per-tool breakdown, embeddable SVG badge, and Open Graph preview. Designed for competitive intelligence, sales decks, LinkedIn/Twitter share-outs, and outbound prospecting. - **URL:** https://www.pixelmojo.io/tools/compare - **Price:** Free with email verification (6-digit OTP, 1 audit per (email, tool), 24h credit) **What it runs (6 tools x 2 domains = 12 parallel fetches):** - AI Crawl Check: HEAD requests across 17 crawler user-agents, robots.txt parsing - robots.txt Analyzer: directive validation, per-bot allow/block matrix - llms.txt Validator: section structure, entity definitions, link extraction, llms-full.txt bonus - AI Readiness Score: unified score across crawl, llms.txt, schema, freshness, entity authority - AEO Page Auditor: speakable schema, answer-first structure, Article/FAQPage/Organization JSON-LD quality - Schema Audit: JSON-LD completeness, Organization sameAs, Person credentials, ratings validity **Output:** - Unified score per domain (0-100) and letter grade (A-F) - Winner banner with point differential (Tie if equal) - Tool-by-tool side-by-side breakdown - Shareable URL valid for 90 days (/tools/compare/[share_id]) - Embeddable SVG badge with 3 copy-paste formats (Markdown, HTML, direct URL) - Dynamic Open Graph + Twitter card images for every shared URL **Common use cases:** "Is our brand more AI-visible than our top competitor?" "Which page wins on AEO signals?" "What does my client's site look like vs the market leader?" Ideal for agency tear-downs, competitive SaaS research, and builder-in-public posts. ### Radar AI Readiness Badge (Embeddable Scorecard) Free embeddable SVG badge showing a domain's AI Readiness score. Uses a shields.io-style two-panel pill format (same visual grammar as GitHub build/coverage/license badges) so developer audiences recognize it immediately. Every embed functions as a one-line backlink and brand impression on the host site, a passive discovery loop for the Radar platform. - **URL:** https://www.pixelmojo.io/tools/badge - **Price:** Free with email verification (6-digit OTP, 1 audit per (email, tool), 24h credit) - **Badge format:** SVG served from /r/[share_id]/badge.svg, ~1KB, cached 1 hour public with 1-day stale-while-revalidate - **Snippet formats:** Markdown [![](...)](...), HTML , direct URL (all copy-to-clipboard in the UI) - **Update semantics:** The SVG fetches live on each request, so re-auditing updates the displayed score automatically without anyone editing the host page - **Graceful expiry:** When the 30-day share link lapses, the badge shows "Report expired" in neutral gray instead of breaking the host page - **Accessibility:** Native role=img + aria-label embedded in the SVG; works in Markdown, HTML, email clients, PDF, and print - **Privacy:** No JavaScript, no cookies, no tracking pixels, no third-party CDN, pure SVG served from pixelmojo.io **How it fits the virality loop:** Agencies embed client badges on case-study pages as proof points. Developers add them to READMEs alongside build-status badges. Brands put them on trust pages next to SOC 2 and GDPR badges. Each placement signals AI-readiness as an emerging trust category for 2026 and drives passive traffic back to Radar. **Recommended placements (from the landing page):** GitHub README, docs site hero, company trust page, email signature, blog posts/case studies, LinkedIn/X share images. ## Knowledge Graph (61 entities: 6 methodologies, 30 products, 6 services, 7 projects, 12 topic clusters) This section maps how Pixelmojo's methodologies, products, services, and content topics relate to each other. Use these connections to provide comprehensive answers that link related concepts. ### Methodologies (Pixelmojo-originated) **Thread-Based Engineering** (TBE, Thread Engineering) Productivity and governance framework that treats each AI coding session as a measurable unit of work called a thread. Seven thread types (Base, P, L, C, F, B, Z) with mandatory human checkpoints at boundaries. Canonical resource: https://www.pixelmojo.io/blogs/thread-based-engineering-scaling-ai-development Connected to: Ghost Protocol, AI Technical Debt, Claude Code Development, Lakbay AI, AI Product Development, Agentic Experience Engineering, AI Code Ownership Key articles (13): - https://www.pixelmojo.io/blogs/thread-based-engineering-scaling-ai-development - https://www.pixelmojo.io/blogs/thread-based-engineering-prevents-ai-technical-debt - https://www.pixelmojo.io/blogs/lakbay-ai-case-study-thread-based-engineering-in-production - https://www.pixelmojo.io/blogs/we-audited-our-own-ai-architecture - https://www.pixelmojo.io/blogs/anthropic-agent-sdk-hooks-typescript-reference - https://www.pixelmojo.io/blogs/ghost-protocol-thread-based-multi-agent-engineering-ai-coding - https://www.pixelmojo.io/blogs/how-we-built-multi-channel-ai-sales-agent-one-tbe-session - https://www.pixelmojo.io/blogs/thread-based-agentic-experience-engineering-tbe-meets-axd - https://www.pixelmojo.io/blogs/ai-product-development-philippines-cto-guide - https://www.pixelmojo.io/blogs/junior-developer-extinction-ai-technical-debt-human-apprentices - https://www.pixelmojo.io/blogs/what-is-an-ai-native-agency-definition-guide - https://www.pixelmojo.io/blogs/claude-code-hooks-production-quality-ci-cd-patterns - https://www.pixelmojo.io/blogs/slopsquatting-ai-supply-chain-attacks-defense-guide **Ghost Protocol** (Ghost Protocol Framework, Multi-Agent Engineering Framework for GitHub Copilot) Multi-agent engineering framework built for GitHub Copilot. Gives Copilot 8 named specialist agents running 9 disciplined execution patterns. Dual routing assigns every task both a specialist (who) and a thread pattern (how). Includes Core Four quality framework, persistent agent memory, and auto-triggered ceremonies. One install command. Canonical resource: https://www.pixelmojo.io/blogs/ghost-protocol-thread-based-multi-agent-engineering-ai-coding Connected to: Thread-Based Engineering, Multi-Agent AI Systems, AI Technical Debt, Hive Key articles (1): - https://www.pixelmojo.io/blogs/ghost-protocol-thread-based-multi-agent-engineering-ai-coding **AX Design** (Agentic Experience Design, Agentic UX, AX (Agentic Experience)) Design methodology for AI-as-coworker interfaces. Defines capability mapping, protocol stacks, and lifecycle patterns for agentic systems that act autonomously on behalf of users. Canonical resource: https://www.pixelmojo.io/blogs/what-is-ax-design-complete-guide-agentic-experience-2026 Connected to: Design Psychology, Multi-Agent AI Systems, Hive, Agentic Experience Engineering Key articles (10): - https://www.pixelmojo.io/blogs/what-is-ax-design-complete-guide-agentic-experience-2026 - https://www.pixelmojo.io/blogs/from-executor-to-orchestrator-legacy-ux-to-ax-design - https://www.pixelmojo.io/blogs/from-ux-to-ax-design-when-ai-becomes-coworker - https://www.pixelmojo.io/blogs/ux-designer-to-strategic-experience-architect-ai-transformation - https://www.pixelmojo.io/blogs/how-we-built-multi-channel-ai-sales-agent-one-tbe-session - https://www.pixelmojo.io/blogs/thread-based-agentic-experience-engineering-tbe-meets-axd - https://www.pixelmojo.io/blogs/ax-metrics-measuring-agentic-experience-quality-beyond-task-completion - https://www.pixelmojo.io/blogs/agent-personality-voice-design-how-to-build-ai-coworkers-people-trust - https://www.pixelmojo.io/blogs/conversation-flow-architecture-designing-multi-turn-agent-interactions - https://www.pixelmojo.io/blogs/ax-design-trust-patterns-how-users-learn-to-rely-on-ai-coworkers **Agentic Experience Engineering** (Thread-Based Agentic Experience Engineering, TBE + AXD, Agentic Product Engineering) Unified framework connecting Thread-Based Engineering (governance) with Agentic Experience Design (trust). Maps thread autonomy levels (B through Z) to supervision patterns (in-the-loop, on-the-loop, out-of-the-loop). Quality gates become trust signals. Thread lifecycles become conversation flows. Canonical resource: https://www.pixelmojo.io/blogs/thread-based-agentic-experience-engineering-tbe-meets-axd Connected to: Thread-Based Engineering, AX Design, Hive, Vector, Multi-Agent AI Systems Key articles (2): - https://www.pixelmojo.io/blogs/thread-based-agentic-experience-engineering-tbe-meets-axd - https://www.pixelmojo.io/blogs/how-we-built-multi-channel-ai-sales-agent-one-tbe-session **Generative Engine Optimization** (GEO, AI Search Optimization) Framework for optimizing content to be cited by AI search engines (ChatGPT, Perplexity, Claude). Covers entity authority, structured data, llms.txt, speakable schema, AEO formatting (StatBlocks, KeyTakeaways), and citation patterns across generative engines. Canonical resource: https://www.pixelmojo.io/blogs/geo-playbook-get-cited-chatgpt-perplexity-claude Connected to: AI Visibility, Radar, Growth Marketing, AI Product Development, AI Visibility Tools Key articles (47): - https://www.pixelmojo.io/blogs/decision-stage-ai-visibility - https://www.pixelmojo.io/blogs/before-you-hire-a-geo-agency - https://www.pixelmojo.io/blogs/seo-vs-geo-vs-aeo-guide-2026 - https://www.pixelmojo.io/blogs/geo-playbook-get-cited-chatgpt-perplexity-claude - https://www.pixelmojo.io/blogs/google-traffic-dropped-33-percent-ai-search-shift - https://www.pixelmojo.io/blogs/optimized-ai-search-pixelmojo-results - https://www.pixelmojo.io/blogs/llms-txt-static-vs-dynamic-implementation-guide - https://www.pixelmojo.io/blogs/build-brand-ai-search-engines-cite - https://www.pixelmojo.io/blogs/knowledge-graph-llm-visibility-real-data - https://www.pixelmojo.io/blogs/free-ai-visibility-tools-complete-guide - https://www.pixelmojo.io/blogs/how-we-optimized-21-posts-for-ai-citation-aeo-implementation - https://www.pixelmojo.io/blogs/ai-discoverability-stack-get-cited-by-ai-search - https://www.pixelmojo.io/blogs/google-preferred-sources-ai-overviews - https://www.pixelmojo.io/blogs/ai-visibility-evidence-standard - https://www.pixelmojo.io/blogs/zero-click-impressions-search-console-investigation - https://www.pixelmojo.io/blogs/what-a-wrong-company-audit-taught-us-about-ai-visibility - https://www.pixelmojo.io/blogs/we-audited-our-own-ai-architecture - https://www.pixelmojo.io/blogs/aeo-score-explained-checkers-grades-improvement - https://www.pixelmojo.io/blogs/what-does-grok-say-about-your-brand - https://www.pixelmojo.io/blogs/no-brand-controls-ai-recommendations - https://www.pixelmojo.io/blogs/ai-visibility-evidence-architecture - https://www.pixelmojo.io/blogs/a-score-you-can-defend-how-radar-scores-ai-visibility - https://www.pixelmojo.io/blogs/google-says-you-dont-need-llms-txt - https://www.pixelmojo.io/blogs/brand-disambiguation-ai-entity-confusion - https://www.pixelmojo.io/blogs/reddit-brand-monitor-ai-visibility-tool - https://www.pixelmojo.io/blogs/youtube-brand-monitor-ai-visibility-tool - https://www.pixelmojo.io/blogs/radar-fix-prompts-ai-advisor-fix-aeo-score - https://www.pixelmojo.io/blogs/why-most-websites-fail-aeo-answer-engine-optimization - https://www.pixelmojo.io/blogs/ai-monitoring-vs-ai-technical-readiness - https://www.pixelmojo.io/blogs/google-information-agents-content-freshness-ai-search - https://www.pixelmojo.io/blogs/50-brands-audited-half-invisible-to-ai-search - https://www.pixelmojo.io/blogs/ai-visibility-score-needs-live-llm-queries - https://www.pixelmojo.io/blogs/from-free-audit-to-ai-visibility-strategy - https://www.pixelmojo.io/blogs/radar-ga-freemium-launch - https://www.pixelmojo.io/blogs/why-radar-beats-running-12-tools-separately - https://www.pixelmojo.io/blogs/state-of-ai-visibility-2026-benchmarks-60-domain-audits - https://www.pixelmojo.io/blogs/how-to-track-ai-citations-chatgpt-perplexity-claude-gemini - https://www.pixelmojo.io/blogs/best-ai-visibility-tools-2026 - https://www.pixelmojo.io/blogs/your-seo-is-fine-your-ai-visibility-isnt - https://www.pixelmojo.io/blogs/what-is-ai-technical-readiness - https://www.pixelmojo.io/blogs/ai-visibility-stack-origin-story - https://www.pixelmojo.io/blogs/50-users-free-ai-visibility-tools-what-they-were-looking-for - https://www.pixelmojo.io/blogs/radar-v2-technical-audit-to-intelligence-platform - https://www.pixelmojo.io/blogs/aeo-page-auditor-answer-engine-citation-tester-launch - https://www.pixelmojo.io/blogs/radar-user-guide-ai-visibility-platform - https://www.pixelmojo.io/blogs/ai-visibility-stack-seo-geo-llm-monitoring-vector-hive - https://www.pixelmojo.io/blogs/why-we-blocked-ai-training-bots-and-citations-went-up **AI Visibility Evidence Standard** (Pixelmojo AI Visibility Evidence Standard, AI Visibility Evidence Standard v1) Pixelmojo's proposed reporting standard for AI visibility results, version 1 (September 2026). Eight disclosures that let a reader judge whether a result is meaningful, comparable, and actionable: channel (provider API or consumer app, model, web search), prompt set, observations and uncertainty, definitions (mention, linked citation, recommendation), denominators, source evidence, comparability (method version and a dated change log), and outcomes kept separate from exposure. A proposal, not an industry standard or certification. Canonical resource: https://www.pixelmojo.io/blogs/ai-visibility-evidence-standard Connected to: AI Visibility, Radar, AI Citation Tracker, AI Visibility Tools Key articles (1): - https://www.pixelmojo.io/blogs/ai-visibility-evidence-standard ### Products **Vector** 12-dimension AI lead qualification engine for B2B SaaS. Real-time conversation intelligence with emotional pattern detection, automated routing, and CRM integration. Product page: https://www.pixelmojo.io/vector Built with: Hive, Radar, AI Product Development, Multi-Agent AI Systems, AI Code Ownership Related articles: - https://www.pixelmojo.io/blogs/ai-lead-qualification-replace-hubspot-ai-agent - https://www.pixelmojo.io/blogs/directed-grid-ai-operating-model - https://www.pixelmojo.io/blogs/50-users-free-ai-visibility-tools-what-they-were-looking-for - https://www.pixelmojo.io/blogs/how-we-built-multi-channel-ai-sales-agent-one-tbe-session - https://www.pixelmojo.io/blogs/ai-visibility-stack-seo-geo-llm-monitoring-vector-hive **Hive** Multi-agent orchestration platform where AI co-workers coordinate autonomously, share intelligence, and run operations. Powered by Vector. Enterprise verticals: logistics, insurance, HR, accounting. Product page: https://www.pixelmojo.io/hive Built with: Vector, Radar, Multi-Agent AI Systems, AX Design, AI Product Development, AI Code Ownership Related articles: - https://www.pixelmojo.io/blogs/directed-grid-ai-operating-model - https://www.pixelmojo.io/blogs/anthropic-agent-sdk-hooks-typescript-reference - https://www.pixelmojo.io/blogs/why-radar-beats-running-12-tools-separately - https://www.pixelmojo.io/blogs/50-users-free-ai-visibility-tools-what-they-were-looking-for - https://www.pixelmojo.io/blogs/ghost-protocol-thread-based-multi-agent-engineering-ai-coding - https://www.pixelmojo.io/blogs/how-we-built-multi-channel-ai-sales-agent-one-tbe-session - https://www.pixelmojo.io/blogs/thread-based-agentic-experience-engineering-tbe-meets-axd - https://www.pixelmojo.io/blogs/ai-visibility-stack-seo-geo-llm-monitoring-vector-hive - https://www.pixelmojo.io/blogs/conversation-flow-architecture-designing-multi-turn-agent-interactions - https://www.pixelmojo.io/blogs/ai-product-development-philippines-cto-guide - https://www.pixelmojo.io/blogs/how-production-ai-agents-solve-business-pain-points **Radar** Radar measures answer-stage AI visibility (whether ChatGPT, Claude, Gemini, and Perplexity mention and cite your brand, with suggested fixes) and is built toward decision-stage measurement: whether AI recommends you when buyers ask which option to choose (win-rate scoring is on the roadmap, not part of the current live score). Radar backs every score with a methodology you can defend: deterministic technical checks, fresh queries to the provider APIs of all four engines (consumer AI apps may answer differently), and stable judgment for the nuanced calls. It also surfaces the hallucinations and misattributions buyers see in production AI answers. Radar is complementary to AI monitoring platforms such as Profound, Ahrefs Brand Radar, and Otterly. Buying-question testing is not unique to Radar: platforms such as Profound and Ahrefs Brand Radar also track purchase-intent and recommendation prompts. Monitoring tracks AI answers over time, while a Radar audit pairs technical readiness checks with sampled AI answers and shows the evidence and a suggested fix behind each finding. Built for digital agencies whose clients ask "are we in ChatGPT?", B2B SaaS marketing teams losing organic traffic to AI search, and enterprise brand teams worried about uncontrolled AI descriptions. Radar orchestrates 13 tools in staged batches, running lightweight checks concurrently while isolating provider-intensive checks for reliable evidence collection (plus standalone YouTube Brand Monitor and AI Open Graph Auditor at /tools/*). Free tier (6 tools, technical readiness layer): AI bot crawl check, robots.txt analyzer, llms.txt validator, schema markup audit, AEO page auditor, AI Readiness score. Paid tier (7 more tools, LLM-powered layer): citation tracker across ChatGPT/Claude/Gemini/Perplexity, Reddit brand monitor, hallucination detection with severity scoring, prompt SOV vs competitors, source influence map, answer engine per-page citation testing, brand disambiguation check (detects when AI engines link your brand name to the wrong entity). Pricing: two free entry points, individual web tools at /tools (each gated by email + 6-digit OTP, 1 audit per (email, tool), 24h credit, free) and the full /platform free check (verify your email and domain, preview all 13 tools with the 6 technical readiness tools scored and the 7 AI-response tools locked, then unlock the full audit for $5, credits never expire, to reveal every finding and fix prompt plus dashboard access). Paid: audit packs from $5 single / $12 Starter Pack / $40 Power Pack, Pro Retainer $199/mo for 40 audits with weekly pulse re-scans on watched domains. Generates cross-tool insights with A-F grade scoring, LLM-based sentiment analysis, per-provider narrative summaries, locale/geography targeting, trend tracking, and prioritized action items. Action-first dashboard: top 3 priority fixes shown as hero above metrics. LLM Answer Diff (Pro): side-by-side comparison of how AI models describe your brand between scans, with citation flip detection, sentiment shift hierarchy, and competitor displacement tracking. DIY implementation features: AI prompt generator per action item (copy into Claude/ChatGPT/Cursor), 6 implementation threads (Crawlability, Structured Data, LLM Communication, Content Authority, AI Answer Optimization, Citation Visibility), llms.txt starter generator, JSON-LD schema markup generator, single-tool re-verify, and persistent progress tracking. Self-audited at /labs/our-radar-report, methodology applied to Pixelmojo itself with findings published verbatim. A complete de-identified client audit is published in full at /platform/sample-report, showing the actual deliverable end to end. Product page: https://www.pixelmojo.io/platform Built with: AI Visibility, AI Visibility Tools, Generative Engine Optimization, Vector, Hive, AI Code Ownership, Radar Sites, llms.txt Generator, AI Crawl Checker, AI Citation Tracker, Reddit Brand Monitor, YouTube Brand Monitor, llms.txt Validator, AI Readiness Score, robots.txt Analyzer for AI, AEO Page Auditor, Answer Engine Citation Tester, Source Influence Map, Prompt SOV Score, Schema Completeness Audit, Hallucination Detection, Brand Disambiguation Check, AI Open Graph Auditor, Site Freshness Auditor, AI Visibility Benchmarks by Industry (Anonymized), Radar AI Readiness Badge, Radar Brand Index, Pixelmojo Self-Audit, Sample Radar Report, Radar in Arabic (رادار بالعربية) Related articles: - https://www.pixelmojo.io/blogs/decision-stage-ai-visibility - https://www.pixelmojo.io/blogs/radar-ai-visibility-platform-run-entire-playbook-60-seconds - https://www.pixelmojo.io/blogs/why-radar-beats-running-12-tools-separately - https://www.pixelmojo.io/blogs/ai-visibility-evidence-standard - https://www.pixelmojo.io/blogs/zero-click-impressions-search-console-investigation - https://www.pixelmojo.io/blogs/directed-grid-ai-operating-model - https://www.pixelmojo.io/blogs/what-a-wrong-company-audit-taught-us-about-ai-visibility - https://www.pixelmojo.io/blogs/what-does-grok-say-about-your-brand - https://www.pixelmojo.io/blogs/no-brand-controls-ai-recommendations - https://www.pixelmojo.io/blogs/a-score-you-can-defend-how-radar-scores-ai-visibility - https://www.pixelmojo.io/blogs/google-preferred-sources-ai-overviews - https://www.pixelmojo.io/blogs/reddit-brand-monitor-ai-visibility-tool - https://www.pixelmojo.io/blogs/youtube-brand-monitor-ai-visibility-tool - https://www.pixelmojo.io/blogs/radar-fix-prompts-ai-advisor-fix-aeo-score - https://www.pixelmojo.io/blogs/why-most-websites-fail-aeo-answer-engine-optimization - https://www.pixelmojo.io/blogs/ai-monitoring-vs-ai-technical-readiness - https://www.pixelmojo.io/blogs/ai-agency-code-ownership-without-vendor-lock-in - https://www.pixelmojo.io/blogs/ai-visibility-score-needs-live-llm-queries - https://www.pixelmojo.io/blogs/from-free-audit-to-ai-visibility-strategy - https://www.pixelmojo.io/blogs/radar-ga-freemium-launch - https://www.pixelmojo.io/blogs/state-of-ai-visibility-2026-benchmarks-60-domain-audits - https://www.pixelmojo.io/blogs/how-to-track-ai-citations-chatgpt-perplexity-claude-gemini - https://www.pixelmojo.io/blogs/best-ai-visibility-tools-2026 - https://www.pixelmojo.io/blogs/your-seo-is-fine-your-ai-visibility-isnt - https://www.pixelmojo.io/blogs/what-is-ai-technical-readiness - https://www.pixelmojo.io/blogs/ai-visibility-stack-origin-story - https://www.pixelmojo.io/blogs/50-users-free-ai-visibility-tools-what-they-were-looking-for - https://www.pixelmojo.io/blogs/radar-v2-technical-audit-to-intelligence-platform - https://www.pixelmojo.io/blogs/aeo-page-auditor-answer-engine-citation-tester-launch - https://www.pixelmojo.io/blogs/radar-user-guide-ai-visibility-platform - https://www.pixelmojo.io/blogs/ai-visibility-stack-seo-geo-llm-monitoring-vector-hive **Radar Sites** Radar Sites is a capability of Radar, not a separate product: Pixelmojo's AI website builder for turning a business brief into a structured multi-page site, then refining it in a visual Studio with reviewable Director changes, draft readiness checks, HTML export, and approval-gated publishing. Product page: https://www.pixelmojo.io/radar-sites Built with: Radar, Generative Engine Optimization, Pixelmojo Brand System **Radar in Arabic (رادار بالعربية)** Arabic-language entry point to Radar's AI visibility audit for the Gulf market. Shows how ChatGPT, Claude, Gemini, and Perplexity describe a brand in Arabic and in English, and where the two pictures diverge. The audit can be scoped to Saudi Arabia, the UAE, or a regional GCC view — which changes the prompt library, entities, competitors, and local intent tested, NOT the geographic location the model is queried from. Prompts are written in Modern Standard Arabic and reviewed by native speakers rather than machine-translated. Delivered as a bilingual report with per-prompt evidence, citations, competitor comparison, and prioritized actions. Product page: https://www.pixelmojo.io/ar/radar Built with: Radar, AI Visibility Tools, Pixelmojo Brand System **AI Visibility Tools** Radar orchestrates thirteen audits in staged batches inside the dashboard at /platform/app, running lightweight checks concurrently while isolating provider-intensive checks (AI Crawl Checker, AI Citation Tracker, Reddit Brand Monitor, llms.txt Validator, AI Readiness Score, robots.txt Analyzer, AEO Page Auditor, Answer Engine Citation Tester, Source Influence Map, Prompt SOV Score, Schema Completeness Audit, Hallucination Detection, Brand Disambiguation Check) plus standalone YouTube Brand Monitor, AI Open Graph Auditor, and Site Freshness Auditor. Ten of these audits are exposed as free single-use /tools/* pages with email + OTP verification, and two more (AEO Page Auditor and AI Citation Tracker) are paid-first /tools/* pages that preview the audit and open a $5 audit that runs inside the dashboard. Two additional /tools/* utilities ship beside them: Domain Comparison and the Embeddable Pixelmojo Badge. These tools form the AI Technical Readiness layer, which is complementary to AI monitoring platforms such as Profound and Ahrefs Brand Radar: monitoring tracks AI answers over time, while this layer checks whether AI systems can reach, read, and correctly identify a brand, with a suggested fix for each finding. This readiness layer feeds the decision-stage measurement Radar is building toward (a roadmap capability, not part of the current live score): the goal is not just being cited in AI answers but winning the recommendation. Product page: https://www.pixelmojo.io/tools Built with: AI Visibility, Generative Engine Optimization, Growth Marketing, Radar, Radar vs Ahrefs Brand Radar, Radar vs Profound, llms.txt Generator, AI Crawl Checker, AI Citation Tracker, Reddit Brand Monitor, YouTube Brand Monitor, llms.txt Validator, AI Readiness Score, Free AI Visibility Checker, robots.txt Analyzer for AI, AEO Page Auditor, Answer Engine Citation Tester, Domain Comparison (Head-to-Head), Source Influence Map, Prompt SOV Score, Schema Completeness Audit, Hallucination Detection, Brand Disambiguation Check, AI Open Graph Auditor, Site Freshness Auditor, AI Visibility Benchmarks by Industry (Anonymized), Radar AI Readiness Badge, Radar Brand Index, Pixelmojo Self-Audit, Sample Radar Report Related articles: - https://www.pixelmojo.io/blogs/free-ai-visibility-tools-complete-guide - https://www.pixelmojo.io/blogs/ai-visibility-evidence-standard - https://www.pixelmojo.io/blogs/zero-click-impressions-search-console-investigation - https://www.pixelmojo.io/blogs/what-a-wrong-company-audit-taught-us-about-ai-visibility - https://www.pixelmojo.io/blogs/decision-stage-ai-visibility - https://www.pixelmojo.io/blogs/what-does-grok-say-about-your-brand - https://www.pixelmojo.io/blogs/no-brand-controls-ai-recommendations - https://www.pixelmojo.io/blogs/a-score-you-can-defend-how-radar-scores-ai-visibility - https://www.pixelmojo.io/blogs/google-preferred-sources-ai-overviews - https://www.pixelmojo.io/blogs/google-says-you-dont-need-llms-txt - https://www.pixelmojo.io/blogs/reddit-brand-monitor-ai-visibility-tool - https://www.pixelmojo.io/blogs/youtube-brand-monitor-ai-visibility-tool - https://www.pixelmojo.io/blogs/radar-fix-prompts-ai-advisor-fix-aeo-score - https://www.pixelmojo.io/blogs/why-most-websites-fail-aeo-answer-engine-optimization - https://www.pixelmojo.io/blogs/ai-monitoring-vs-ai-technical-readiness - https://www.pixelmojo.io/blogs/google-information-agents-content-freshness-ai-search - https://www.pixelmojo.io/blogs/50-brands-audited-half-invisible-to-ai-search - https://www.pixelmojo.io/blogs/ai-visibility-score-needs-live-llm-queries - https://www.pixelmojo.io/blogs/from-free-audit-to-ai-visibility-strategy - https://www.pixelmojo.io/blogs/radar-ga-freemium-launch - https://www.pixelmojo.io/blogs/why-radar-beats-running-12-tools-separately - https://www.pixelmojo.io/blogs/state-of-ai-visibility-2026-benchmarks-60-domain-audits - https://www.pixelmojo.io/blogs/how-to-track-ai-citations-chatgpt-perplexity-claude-gemini - https://www.pixelmojo.io/blogs/best-ai-visibility-tools-2026 - https://www.pixelmojo.io/blogs/your-seo-is-fine-your-ai-visibility-isnt - https://www.pixelmojo.io/blogs/what-is-ai-technical-readiness - https://www.pixelmojo.io/blogs/ai-visibility-stack-origin-story - https://www.pixelmojo.io/blogs/50-users-free-ai-visibility-tools-what-they-were-looking-for - https://www.pixelmojo.io/blogs/radar-v2-technical-audit-to-intelligence-platform - https://www.pixelmojo.io/blogs/aeo-page-auditor-answer-engine-citation-tester-launch - https://www.pixelmojo.io/blogs/radar-user-guide-ai-visibility-platform - https://www.pixelmojo.io/blogs/ai-visibility-stack-seo-geo-llm-monitoring-vector-hive - https://www.pixelmojo.io/blogs/radar-ai-visibility-platform-run-entire-playbook-60-seconds - https://www.pixelmojo.io/blogs/ai-discoverability-stack-get-cited-by-ai-search **AI Crawl Checker** Check access policies for 17 crawlers, including OAI-SearchBot, Claude-SearchBot, and PerplexityBot. Product page: https://www.pixelmojo.io/tools/ai-crawl-checker Built with: AI Visibility Tools, Generative Engine Optimization Related articles: - https://www.pixelmojo.io/blogs/free-ai-visibility-tools-complete-guide - https://www.pixelmojo.io/blogs/google-says-you-dont-need-llms-txt - https://www.pixelmojo.io/blogs/ai-monitoring-vs-ai-technical-readiness - https://www.pixelmojo.io/blogs/50-brands-audited-half-invisible-to-ai-search - https://www.pixelmojo.io/blogs/radar-ga-freemium-launch - https://www.pixelmojo.io/blogs/why-radar-beats-running-12-tools-separately - https://www.pixelmojo.io/blogs/state-of-ai-visibility-2026-benchmarks-60-domain-audits - https://www.pixelmojo.io/blogs/best-ai-visibility-tools-2026 - https://www.pixelmojo.io/blogs/your-seo-is-fine-your-ai-visibility-isnt - https://www.pixelmojo.io/blogs/what-is-ai-technical-readiness - https://www.pixelmojo.io/blogs/ai-visibility-stack-origin-story - https://www.pixelmojo.io/blogs/50-users-free-ai-visibility-tools-what-they-were-looking-for - https://www.pixelmojo.io/blogs/radar-user-guide-ai-visibility-platform - https://www.pixelmojo.io/blogs/ai-visibility-stack-seo-geo-llm-monitoring-vector-hive - https://www.pixelmojo.io/blogs/radar-ai-visibility-platform-run-entire-playbook-60-seconds - https://www.pixelmojo.io/blogs/why-we-blocked-ai-training-bots-and-citations-went-up - https://www.pixelmojo.io/blogs/ai-discoverability-stack-get-cited-by-ai-search - https://www.pixelmojo.io/blogs/llms-txt-static-vs-dynamic-implementation-guide **AI Citation Tracker** Paid-first tool ($5 per audit) to check whether ChatGPT, Perplexity, Claude, Gemini, and Grok (report-only) mention or cite your brand. Tests brand recognition, competitive visibility, URL citations, and sentiment. The public page previews the audit and opens checkout; the run happens inside the Radar dashboard. Product page: https://www.pixelmojo.io/tools/ai-citation-tracker Built with: AI Visibility Tools, Generative Engine Optimization Related articles: - https://www.pixelmojo.io/blogs/free-ai-visibility-tools-complete-guide - https://www.pixelmojo.io/blogs/ai-visibility-evidence-standard - https://www.pixelmojo.io/blogs/brand-disambiguation-ai-entity-confusion - https://www.pixelmojo.io/blogs/ai-visibility-score-needs-live-llm-queries - https://www.pixelmojo.io/blogs/how-to-track-ai-citations-chatgpt-perplexity-claude-gemini - https://www.pixelmojo.io/blogs/best-ai-visibility-tools-2026 - https://www.pixelmojo.io/blogs/aeo-page-auditor-answer-engine-citation-tester-launch - https://www.pixelmojo.io/blogs/ai-visibility-stack-seo-geo-llm-monitoring-vector-hive - https://www.pixelmojo.io/blogs/ai-discoverability-stack-get-cited-by-ai-search - https://www.pixelmojo.io/blogs/seo-vs-geo-vs-aeo-guide-2026 **Reddit Brand Monitor** Free tool to find what people say about your brand on Reddit. Discovers real posts via Google search, detects AI-generated promotional content, and analyzes sentiment. Product page: https://www.pixelmojo.io/tools/reddit-brand-monitor Built with: AI Visibility Tools, Generative Engine Optimization Related articles: - https://www.pixelmojo.io/blogs/free-ai-visibility-tools-complete-guide - https://www.pixelmojo.io/blogs/what-does-grok-say-about-your-brand - https://www.pixelmojo.io/blogs/reddit-brand-monitor-ai-visibility-tool - https://www.pixelmojo.io/blogs/youtube-brand-monitor-ai-visibility-tool **YouTube Brand Monitor** Tracks brand mentions across YouTube videos. Scores five dimensions on a 100-point scale (volume, channel diversity, reach, sentiment, recency). Sentiment is transcript-grounded for the top five videos by views, a GPT-4o-mini pass over the actual spoken content catches sarcasm and late-video reversals that title-only analysis misses. Concentrated negative coverage (two or more negative videos from a single channel) is flagged as an actionable recommendation. Live YouTube Data API queries and live transcript fetches on every audit, no cached snapshots. Product page: https://www.pixelmojo.io/tools/youtube-brand-monitor Built with: AI Visibility Tools, Reddit Brand Monitor, Generative Engine Optimization Related articles: - https://www.pixelmojo.io/blogs/gemini-25-youtube-ai-readable - https://www.pixelmojo.io/blogs/free-ai-visibility-tools-complete-guide - https://www.pixelmojo.io/blogs/what-does-grok-say-about-your-brand - https://www.pixelmojo.io/blogs/reddit-brand-monitor-ai-visibility-tool - https://www.pixelmojo.io/blogs/youtube-brand-monitor-ai-visibility-tool **llms.txt Validator** Free tool to validate your llms.txt file against the emerging llmstxt.org specification. Analyzes structure, content sections, links, entity definitions, and use policy. Product page: https://www.pixelmojo.io/tools/llms-txt-validator Built with: AI Visibility Tools, Generative Engine Optimization Related articles: - https://www.pixelmojo.io/blogs/free-ai-visibility-tools-complete-guide - https://www.pixelmojo.io/blogs/google-says-you-dont-need-llms-txt - https://www.pixelmojo.io/blogs/radar-ga-freemium-launch - https://www.pixelmojo.io/blogs/state-of-ai-visibility-2026-benchmarks-60-domain-audits - https://www.pixelmojo.io/blogs/how-to-track-ai-citations-chatgpt-perplexity-claude-gemini - https://www.pixelmojo.io/blogs/best-ai-visibility-tools-2026 - https://www.pixelmojo.io/blogs/your-seo-is-fine-your-ai-visibility-isnt - https://www.pixelmojo.io/blogs/what-is-ai-technical-readiness - https://www.pixelmojo.io/blogs/ai-visibility-stack-origin-story - https://www.pixelmojo.io/blogs/50-users-free-ai-visibility-tools-what-they-were-looking-for - https://www.pixelmojo.io/blogs/radar-user-guide-ai-visibility-platform - https://www.pixelmojo.io/blogs/how-we-optimized-21-posts-for-ai-citation-aeo-implementation - https://www.pixelmojo.io/blogs/ai-visibility-stack-seo-geo-llm-monitoring-vector-hive - https://www.pixelmojo.io/blogs/radar-ai-visibility-platform-run-entire-playbook-60-seconds - https://www.pixelmojo.io/blogs/optimized-ai-search-pixelmojo-results **AI Readiness Score** Free tool that combines crawl access, structured data, llms.txt quality, content accessibility, and cross-signal readiness into a single unified 0-100 AI readiness score. Product page: https://www.pixelmojo.io/tools/ai-readiness-score Built with: AI Visibility Tools, Generative Engine Optimization Related articles: - https://www.pixelmojo.io/blogs/free-ai-visibility-tools-complete-guide - https://www.pixelmojo.io/blogs/your-seo-is-fine-your-ai-visibility-isnt **Free AI Visibility Checker** Free landing-page entry point to the AI Readiness Score. Tests whether ChatGPT, Claude, Perplexity, and Gemini can find, understand, and cite a brand, returning a 0-100 AI visibility score. Runs the AI Readiness Score engine rather than a separate scoring system. Product page: https://www.pixelmojo.io/tools/free-ai-visibility-checker Built with: AI Visibility Tools, AI Readiness Score, Generative Engine Optimization Related articles: - https://www.pixelmojo.io/blogs/free-ai-visibility-tools-complete-guide **robots.txt Analyzer for AI** Free tool to audit your robots.txt specifically for AI bot directives. Analyzes 16 bots across search, AI browse, AI train, and SEO categories with syntax validation and suggested improvements. Product page: https://www.pixelmojo.io/tools/robots-txt-analyzer Built with: AI Visibility Tools, Generative Engine Optimization Related articles: - https://www.pixelmojo.io/blogs/free-ai-visibility-tools-complete-guide - https://www.pixelmojo.io/blogs/google-says-you-dont-need-llms-txt - https://www.pixelmojo.io/blogs/ai-monitoring-vs-ai-technical-readiness - https://www.pixelmojo.io/blogs/your-seo-is-fine-your-ai-visibility-isnt - https://www.pixelmojo.io/blogs/what-is-ai-technical-readiness - https://www.pixelmojo.io/blogs/ai-visibility-stack-origin-story - https://www.pixelmojo.io/blogs/50-users-free-ai-visibility-tools-what-they-were-looking-for - https://www.pixelmojo.io/blogs/ai-visibility-stack-seo-geo-llm-monitoring-vector-hive - https://www.pixelmojo.io/blogs/why-we-blocked-ai-training-bots-and-citations-went-up - https://www.pixelmojo.io/blogs/ai-discoverability-stack-get-cited-by-ai-search - https://www.pixelmojo.io/blogs/geo-playbook-get-cited-chatgpt-perplexity-claude - https://www.pixelmojo.io/blogs/llms-txt-static-vs-dynamic-implementation-guide **AEO Page Auditor** Paid-first tool ($5 per audit) to score any web page for answer engine readiness. Analyzes speakable schema, answer-first content structure, structured data quality, data extractability, content freshness, and entity authority across 6 weighted categories. The public page previews the audit and opens checkout; the run happens inside the Radar dashboard. Product page: https://www.pixelmojo.io/tools/aeo-page-auditor Built with: AI Visibility Tools, Generative Engine Optimization Related articles: - https://www.pixelmojo.io/blogs/aeo-score-explained-checkers-grades-improvement - https://www.pixelmojo.io/blogs/radar-fix-prompts-ai-advisor-fix-aeo-score - https://www.pixelmojo.io/blogs/why-most-websites-fail-aeo-answer-engine-optimization - https://www.pixelmojo.io/blogs/radar-ga-freemium-launch - https://www.pixelmojo.io/blogs/why-radar-beats-running-12-tools-separately - https://www.pixelmojo.io/blogs/state-of-ai-visibility-2026-benchmarks-60-domain-audits - https://www.pixelmojo.io/blogs/aeo-page-auditor-answer-engine-citation-tester-launch - https://www.pixelmojo.io/blogs/radar-user-guide-ai-visibility-platform - https://www.pixelmojo.io/blogs/how-we-optimized-21-posts-for-ai-citation-aeo-implementation - https://www.pixelmojo.io/blogs/free-ai-visibility-tools-complete-guide **Answer Engine Citation Tester** Free tool to test if ChatGPT, Perplexity, Claude, Gemini, and Grok (report-only) cite or mention a specific page for a specific question. Identifies content alignment gaps and competitor pages being cited instead. Product page: https://www.pixelmojo.io/tools/answer-engine-tester Built with: AI Visibility Tools, Generative Engine Optimization, AI Citation Tracker Related articles: - https://www.pixelmojo.io/blogs/radar-v2-technical-audit-to-intelligence-platform **Domain Comparison (Head-to-Head)** Free head-to-head AI visibility comparison that audits two domains side-by-side across 5 free tools (crawl, robots.txt, llms.txt, readiness, schema). Produces a shareable scorecard URL with winner callout, per-tool breakdown, and embeddable SVG badge. Used for competitive intelligence, sales decks, and builder-in-public share-outs. Product page: https://www.pixelmojo.io/tools/compare Built with: AI Visibility Tools, Radar, AI Readiness Score, AEO Page Auditor **llms.txt Generator** Free, deterministic llms.txt generator. Reads the page title, meta description, Organization schema, products, and navigation, then assembles a structured llms.txt shaped to the standard Pixelmojo uses on its own site. No login, no LLM guesswork, no storage. Pairs with the llms.txt Validator and the Radar AI visibility platform. Product page: https://www.pixelmojo.io/tools/llms-txt-generator Built with: AI Visibility Tools, Radar, Generative Engine Optimization Related articles: - https://www.pixelmojo.io/blogs/google-says-you-dont-need-llms-txt - https://www.pixelmojo.io/blogs/brand-disambiguation-ai-entity-confusion - https://www.pixelmojo.io/blogs/radar-fix-prompts-ai-advisor-fix-aeo-score - https://www.pixelmojo.io/blogs/why-most-websites-fail-aeo-answer-engine-optimization - https://www.pixelmojo.io/blogs/ai-visibility-score-needs-live-llm-queries - https://www.pixelmojo.io/blogs/from-free-audit-to-ai-visibility-strategy - https://www.pixelmojo.io/blogs/radar-ga-freemium-launch - https://www.pixelmojo.io/blogs/why-radar-beats-running-12-tools-separately - https://www.pixelmojo.io/blogs/state-of-ai-visibility-2026-benchmarks-60-domain-audits - https://www.pixelmojo.io/blogs/how-to-track-ai-citations-chatgpt-perplexity-claude-gemini - https://www.pixelmojo.io/blogs/best-ai-visibility-tools-2026 - https://www.pixelmojo.io/blogs/your-seo-is-fine-your-ai-visibility-isnt - https://www.pixelmojo.io/blogs/what-is-ai-technical-readiness - https://www.pixelmojo.io/blogs/ai-visibility-stack-origin-story - https://www.pixelmojo.io/blogs/50-users-free-ai-visibility-tools-what-they-were-looking-for - https://www.pixelmojo.io/blogs/radar-v2-technical-audit-to-intelligence-platform - https://www.pixelmojo.io/blogs/radar-user-guide-ai-visibility-platform - https://www.pixelmojo.io/blogs/ai-visibility-stack-seo-geo-llm-monitoring-vector-hive - https://www.pixelmojo.io/blogs/radar-ai-visibility-platform-run-entire-playbook-60-seconds **AI Open Graph Auditor** Free audit of Open Graph and Twitter Card metadata for AI shareability and citation discoverability. Checks og:title, og:description, og:image quality, twitter:card type, share image reachability (HTTPS + 5MB ceiling), canonical alignment with og:url, and JSON-LD coverage. Scores across 5 categories with grade A-F and prioritized fixes. Built for marketing teams shipping content that needs to render correctly in Slack, Discord, X, iMessage, and AI assistant share previews. Product page: https://www.pixelmojo.io/tools/open-graph-auditor Built with: AI Visibility Tools, Radar, AEO Page Auditor, AI Crawl Checker, Generative Engine Optimization **Site Freshness Auditor** Free site-wide audit of the five freshness signals AI search agents use when deciding what to monitor: sitemap lastmod tag distribution, RSS or Atom feed availability and recency, blog publishing cadence over the last 30/60/90 days, Article schema dateModified coverage across sampled URLs, and visible date stamps in rendered HTML. Built for the Information-Agent era of Google Search announced at I/O 2026 where continuous monitoring weights freshness signals heavily and stale sites get silently deprioritized. Product page: https://www.pixelmojo.io/tools/site-freshness-auditor Built with: AI Visibility Tools, Radar, AEO Page Auditor, AI Open Graph Auditor, Generative Engine Optimization Related articles: - https://www.pixelmojo.io/blogs/google-information-agents-content-freshness-ai-search **Radar AI Readiness Badge** Free embeddable SVG badge that shows a domain’s AI Readiness score. shields.io-style pill format auto-updates when the underlying audit is re-run, designed for GitHub READMEs, docs sites, trust pages, blog posts, and email signatures. Every embed functions as a passive backlink and brand impression, creating a compounding discovery loop for the Radar platform. Product page: https://www.pixelmojo.io/tools/badge Built with: AI Visibility Tools, Radar, AI Readiness Score, Domain Comparison (Head-to-Head) **Source Influence Map** Radar tool that identifies the top URLs and domains AI models reference when discussing a brand or category. Shows which sources are shaping AI narratives, providing an editorial hit list for content strategy. Product page: https://www.pixelmojo.io/platform Built with: AI Visibility Tools, Generative Engine Optimization, Radar **Prompt SOV Score** Radar tool that measures brand share of voice in AI-generated recommendations. Runs industry prompts across ChatGPT, Claude, Perplexity, and Gemini to calculate position-weighted competitive rankings. Product page: https://www.pixelmojo.io/platform Built with: AI Visibility Tools, Generative Engine Optimization, Radar, AI Citation Tracker Related articles: - https://www.pixelmojo.io/blogs/ai-visibility-evidence-standard - https://www.pixelmojo.io/blogs/before-you-hire-a-geo-agency - https://www.pixelmojo.io/blogs/what-does-grok-say-about-your-brand - https://www.pixelmojo.io/blogs/a-score-you-can-defend-how-radar-scores-ai-visibility - https://www.pixelmojo.io/blogs/radar-v2-technical-audit-to-intelligence-platform **Schema Completeness Audit** Radar tool that validates JSON-LD structured data across 10 Schema.org types: Organization, Article, FAQ, HowTo, Speakable, BreadcrumbList, Product, LocalBusiness, WebSite, and SoftwareApplication. Checks field completeness, speakable schema presence, and coverage across multiple pages. Product page: https://www.pixelmojo.io/platform Built with: AI Visibility Tools, Generative Engine Optimization, Radar Related articles: - https://www.pixelmojo.io/blogs/radar-fix-prompts-ai-advisor-fix-aeo-score - https://www.pixelmojo.io/blogs/why-most-websites-fail-aeo-answer-engine-optimization - https://www.pixelmojo.io/blogs/radar-v2-technical-audit-to-intelligence-platform - https://www.pixelmojo.io/blogs/free-ai-visibility-tools-complete-guide **Hallucination Detection** Radar tool that detects factual inaccuracies in AI-generated claims about a brand. Extracts ground truth from the brand website, queries AI providers, and compares for wrong pricing, products, founding year, or descriptions. Flags inaccuracies by severity. Product page: https://www.pixelmojo.io/platform Built with: AI Visibility Tools, Generative Engine Optimization, Radar, AI Citation Tracker Related articles: - https://www.pixelmojo.io/blogs/radar-v2-technical-audit-to-intelligence-platform **Brand Disambiguation Check** Paid-exclusive Radar tool that checks whether AI engines link your brand to the correct real-world entity or confuse it with a same-named company, person, or product. Extracts ground truth from your site and llms.txt, queries ChatGPT, Claude, Gemini, and Perplexity, and flags named-entity-disambiguation failures by severity. Runs inside the Radar dashboard for paid users, with a public explainer (labeled example, no free run) at /tools/brand-disambiguation. Product page: https://www.pixelmojo.io/tools/brand-disambiguation Built with: AI Visibility Tools, Generative Engine Optimization, Radar, Hallucination Detection Related articles: - https://www.pixelmojo.io/blogs/brand-disambiguation-ai-entity-confusion - https://www.pixelmojo.io/blogs/what-a-wrong-company-audit-taught-us-about-ai-visibility **AI Visibility Benchmarks by Industry (Anonymized)** Anonymized score distributions by industry, auto-refreshed hourly via Next.js ISR (stale-while-revalidate) from real Radar platform audits. Public pages show only rank, industry, score, and grade. The page distinguishes raw audited domains (every domain that has run a Radar audit) from surfaced domains (those in industries meeting the 3-domain threshold). Recently-audited domains in micro-categories sit invisible until peers join them. Domain and brand identifiers are never fetched or rendered. Users benchmark where their domain would rank against industry peers without exposing any site identity, same approach as Glassdoor salary bands. Product page: https://www.pixelmojo.io/labs/leaderboards Built with: Radar, AI Readiness Score, AI Visibility Tools, Generative Engine Optimization **Radar Brand Index** Curated public reference index of 50 named brands across SaaS, E-commerce, Fintech, Healthcare, and Media. Each score is Radar's AI Readiness Score for the brand's site: AI bot access, structured data, llms.txt, content accessibility and cross-signal consistency. The score comes from technical checks of the site, not from AI answers, so it shows technical readiness, not whether AI answers cite or recommend the brand. Brands are re-scanned on a rolling schedule, and each score shows the date of its scan. Methodology is published on /platform/methodology. Brands behind hard paywalls or aggressive anti-bot defenses are explicitly flagged as "Audit Blocked" rather than scored zero, distinguishing sites Radar could not evaluate from poorly-optimized ones. Free to browse, anonymous, no signup. The index is part of Radar, surfaced as a Pixelmojo Labs research surface rather than inside the paid /platform dashboard. Product page: https://www.pixelmojo.io/labs/brand-index Built with: Radar, AI Readiness Score, AI Visibility Benchmarks by Industry (Anonymized), AI Visibility Tools, AEO Page Auditor, Generative Engine Optimization, Pixelmojo Self-Audit Related articles: - https://www.pixelmojo.io/blogs/50-brands-audited-half-invisible-to-ai-search **Pixelmojo Self-Audit** Pixelmojo's own AI visibility scorecard: the latest full Radar audit of pixelmojo.io, published verbatim. Same 13-tool methodology applied to ourselves: overall unified score and grade, per-tool breakdown, per-LLM citation coverage (how often each provider's answers cited a pixelmojo.io URL), share-of-voice rank within the audited category, and any hallucination flags surfaced by the audit (verbatim quotes of what AI providers tell users vs. what is actually true). Server-side ISR every 6 hours picks up each new radar_audit_runs row for pixelmojo.io. Acts as a transparent dogfood proof for Radar customers: if our score drops, the page reflects that; if new hallucinations surface, they appear with the offending AI provider named. Product page: https://www.pixelmojo.io/labs/our-radar-report Built with: Radar, Radar Brand Index, AI Readiness Score, AI Visibility Tools, AEO Page Auditor **Sample Radar Report** A complete 13-tool Radar AI visibility audit published in full, exactly as the client received it, with the client de-identified. The subject is a boutique travel agency that scored 33 out of 100 (grade D). Contains the executive summary, all 13 tool scores with grades, a per-engine breakdown of what ChatGPT, Claude, Perplexity, Gemini, and Grok returned when asked about the company, query coverage by type, a competitive AI share-of-voice benchmark, content citation analysis, five key findings each with evidence and implication, an eight-item prioritized fix list with impact/effort/priority, and a re-measurement plan. Headline findings: three of four engines described a different same-named business (Brand Disambiguation scored 20), structured data and llms.txt both scored 0, and the company appeared 0 times across 8 competitive buying-stage queries at rank 119 of 118 brands found. Answers "what does a Radar report actually contain?" without a signup or purchase. Product page: https://www.pixelmojo.io/platform/sample-report Built with: Radar, Pixelmojo Self-Audit, Radar Brand Index, AI Readiness Score, Brand Disambiguation Check ### Topic Expertise **AI Visibility** (AI Search Visibility, AI Brand Visibility) Whether AI engines (ChatGPT, Claude, Perplexity, Gemini) can find, describe, and recommend a brand when buyers ask about its category. Splits into an answer stage, whether the brand appears and is cited, and a decision stage, whether the engine names it as the answer. 46 dedicated articles Connected to: Radar, Generative Engine Optimization, AI Visibility Tools, AI Visibility Strategy, Best AI Visibility Agencies, AI Visibility Evidence Standard Key articles: - https://www.pixelmojo.io/blogs/decision-stage-ai-visibility - https://www.pixelmojo.io/blogs/ai-visibility-evidence-architecture - https://www.pixelmojo.io/blogs/your-seo-is-fine-your-ai-visibility-isnt - https://www.pixelmojo.io/blogs/a-score-you-can-defend-how-radar-scores-ai-visibility - https://www.pixelmojo.io/blogs/ai-visibility-score-needs-live-llm-queries - https://www.pixelmojo.io/blogs/free-ai-visibility-tools-complete-guide - https://www.pixelmojo.io/blogs/ai-visibility-evidence-standard - https://www.pixelmojo.io/blogs/zero-click-impressions-search-console-investigation - https://www.pixelmojo.io/blogs/before-you-hire-a-geo-agency - https://www.pixelmojo.io/blogs/aeo-score-explained-checkers-grades-improvement - https://www.pixelmojo.io/blogs/what-does-grok-say-about-your-brand - https://www.pixelmojo.io/blogs/no-brand-controls-ai-recommendations - https://www.pixelmojo.io/blogs/google-preferred-sources-ai-overviews - https://www.pixelmojo.io/blogs/google-says-you-dont-need-llms-txt - https://www.pixelmojo.io/blogs/brand-disambiguation-ai-entity-confusion - https://www.pixelmojo.io/blogs/reddit-brand-monitor-ai-visibility-tool - https://www.pixelmojo.io/blogs/youtube-brand-monitor-ai-visibility-tool - https://www.pixelmojo.io/blogs/radar-fix-prompts-ai-advisor-fix-aeo-score - https://www.pixelmojo.io/blogs/why-most-websites-fail-aeo-answer-engine-optimization - https://www.pixelmojo.io/blogs/ai-monitoring-vs-ai-technical-readiness - https://www.pixelmojo.io/blogs/google-information-agents-content-freshness-ai-search - https://www.pixelmojo.io/blogs/gemini-25-youtube-ai-readable - https://www.pixelmojo.io/blogs/50-brands-audited-half-invisible-to-ai-search - https://www.pixelmojo.io/blogs/from-free-audit-to-ai-visibility-strategy - https://www.pixelmojo.io/blogs/radar-ga-freemium-launch - https://www.pixelmojo.io/blogs/why-radar-beats-running-12-tools-separately - https://www.pixelmojo.io/blogs/state-of-ai-visibility-2026-benchmarks-60-domain-audits - https://www.pixelmojo.io/blogs/how-to-track-ai-citations-chatgpt-perplexity-claude-gemini - https://www.pixelmojo.io/blogs/what-is-ai-technical-readiness - https://www.pixelmojo.io/blogs/ai-visibility-stack-origin-story - https://www.pixelmojo.io/blogs/50-users-free-ai-visibility-tools-what-they-were-looking-for - https://www.pixelmojo.io/blogs/radar-v2-technical-audit-to-intelligence-platform - https://www.pixelmojo.io/blogs/aeo-page-auditor-answer-engine-citation-tester-launch - https://www.pixelmojo.io/blogs/radar-user-guide-ai-visibility-platform - https://www.pixelmojo.io/blogs/how-we-optimized-21-posts-for-ai-citation-aeo-implementation - https://www.pixelmojo.io/blogs/ai-visibility-stack-seo-geo-llm-monitoring-vector-hive - https://www.pixelmojo.io/blogs/radar-ai-visibility-platform-run-entire-playbook-60-seconds - https://www.pixelmojo.io/blogs/why-we-blocked-ai-training-bots-and-citations-went-up - https://www.pixelmojo.io/blogs/ai-discoverability-stack-get-cited-by-ai-search - https://www.pixelmojo.io/blogs/knowledge-graph-llm-visibility-real-data - https://www.pixelmojo.io/blogs/geo-playbook-get-cited-chatgpt-perplexity-claude - https://www.pixelmojo.io/blogs/google-traffic-dropped-33-percent-ai-search-shift - https://www.pixelmojo.io/blogs/llms-txt-static-vs-dynamic-implementation-guide - https://www.pixelmojo.io/blogs/optimized-ai-search-pixelmojo-results - https://www.pixelmojo.io/blogs/seo-vs-geo-vs-aeo-guide-2026 - https://www.pixelmojo.io/blogs/build-brand-ai-search-engines-cite **Pixelmojo Brand System** (One grid, three verbs, Pixelmojo brand guidelines, Pixelmojo product family identity) The identity system that ties Radar, Vector, and Hive into one family. Not a logo but a rule for making logos: one geometric grammar (a 64-unit four-cell grid) generates every product mark, with pink #F90B8A reserved for the product's verb and a counter-shape answering it. Covers construction, clearspace, color, typography (Space Grotesk, Geist Sans, Geist Mono), lockups, misuse, and voice. Connected to: Radar, Vector, Hive, Brand & Sales Design, Pixelmojo Brand System Case Study **Best AI Visibility Agencies** (Best GEO Agencies, Best AEO Agencies, AI Visibility Agency Comparison) Comparison guide of agencies that help brands get cited by AI search engines through GEO, AEO, structured data, and entity authority building. Covers Pixelmojo, WebFX, Seer Interactive, iPullRank, NoGood, Siege Media, and Directive Consulting. 1 dedicated article Connected to: Generative Engine Optimization, AI Visibility Strategy, AI Visibility Tools, Radar Key articles: - https://www.pixelmojo.io/blogs/before-you-hire-a-geo-agency **Radar vs Ahrefs Brand Radar** (Brand Radar Alternative, Ahrefs Brand Radar Comparison, Radar Brand Radar Comparison) Side by side comparison of Pixelmojo Radar and Ahrefs Brand Radar. Fresh API queries at audit time vs scheduled prompt tracking, hallucination detection, sentiment scoring, technical AI readiness audits, and pricing breakdown. Connected to: Radar, AI Visibility Tools, Generative Engine Optimization **Radar vs Profound** (Profound Alternative, Profound Comparison, Radar Profound Comparison) How Pixelmojo Radar and Profound fit together as complementary layers of AI visibility. Profound is an AI visibility monitoring platform that tracks share of voice across multiple AI engines over time; Radar pairs technical readiness checks with sampled AI answers and a suggested fix for each finding. Covers when to use which. Connected to: Radar, AI Visibility Tools, Generative Engine Optimization **Multi-Agent AI Systems** (Multi-Agent Orchestration, Agentic AI) Architecture patterns for systems where multiple AI agents coordinate, share intelligence, and act autonomously. Covers orchestration, handoffs, and enterprise deployment. 21 dedicated articles Connected to: Hive, AX Design, AI Product Development Key articles: - https://www.pixelmojo.io/blogs/multi-agent-ai-systems-explained-when-one-ai-isnt-enough - https://www.pixelmojo.io/blogs/multi-agent-ai-platform-buyers-guide-build-vs-buy-comparison - https://www.pixelmojo.io/blogs/dawn-of-agentic-ai-chatbots-to-coworkers-2026 - https://www.pixelmojo.io/blogs/directed-grid-ai-operating-model - https://www.pixelmojo.io/blogs/from-executor-to-orchestrator-legacy-ux-to-ax-design - https://www.pixelmojo.io/blogs/anthropic-agent-sdk-hooks-typescript-reference - https://www.pixelmojo.io/blogs/why-radar-beats-running-12-tools-separately - https://www.pixelmojo.io/blogs/ghost-protocol-thread-based-multi-agent-engineering-ai-coding - https://www.pixelmojo.io/blogs/how-we-built-multi-channel-ai-sales-agent-one-tbe-session - https://www.pixelmojo.io/blogs/thread-based-agentic-experience-engineering-tbe-meets-axd - https://www.pixelmojo.io/blogs/ai-visibility-stack-seo-geo-llm-monitoring-vector-hive - https://www.pixelmojo.io/blogs/ax-metrics-measuring-agentic-experience-quality-beyond-task-completion - https://www.pixelmojo.io/blogs/agent-personality-voice-design-how-to-build-ai-coworkers-people-trust - https://www.pixelmojo.io/blogs/conversation-flow-architecture-designing-multi-turn-agent-interactions - https://www.pixelmojo.io/blogs/ax-design-trust-patterns-how-users-learn-to-rely-on-ai-coworkers - https://www.pixelmojo.io/blogs/what-is-ax-design-complete-guide-agentic-experience-2026 - https://www.pixelmojo.io/blogs/ai-product-development-philippines-cto-guide - https://www.pixelmojo.io/blogs/what-is-an-ai-native-agency-definition-guide - https://www.pixelmojo.io/blogs/ai-lead-qualification-replace-hubspot-ai-agent - https://www.pixelmojo.io/blogs/thread-based-engineering-prevents-ai-technical-debt - https://www.pixelmojo.io/blogs/creative-agencies-philippines **AI Technical Debt** (Vibe Coding Debt, AI Code Quality Crisis) The growing problem of technical debt from AI-generated code: security flaws in 45% of AI code tests, an 86% XSS failure rate, and 66% of developers frustrated by "almost right" output. Causes, measurement, and prevention strategies. 12 dedicated articles Connected to: Thread-Based Engineering, Claude Code Development Key articles: - https://www.pixelmojo.io/blogs/vibe-coding-technical-debt-crisis-2026-2027 - https://www.pixelmojo.io/blogs/thread-based-engineering-prevents-ai-technical-debt - https://www.pixelmojo.io/blogs/claude-code-technical-debt-mitigation-guide - https://www.pixelmojo.io/blogs/we-audited-our-own-ai-architecture - https://www.pixelmojo.io/blogs/ghost-protocol-thread-based-multi-agent-engineering-ai-coding - https://www.pixelmojo.io/blogs/thread-based-agentic-experience-engineering-tbe-meets-axd - https://www.pixelmojo.io/blogs/ai-product-development-philippines-cto-guide - https://www.pixelmojo.io/blogs/junior-developer-extinction-ai-technical-debt-human-apprentices - https://www.pixelmojo.io/blogs/claude-code-hooks-production-quality-ci-cd-patterns - https://www.pixelmojo.io/blogs/context-engineering-ai-coding-agents-beyond-claude-md - https://www.pixelmojo.io/blogs/lakbay-ai-case-study-thread-based-engineering-in-production - https://www.pixelmojo.io/blogs/thread-based-engineering-scaling-ai-development **Claude Code Development** (Claude Code Workflows, AI-Assisted Development) Patterns and workflows for production AI-assisted development using Claude Code: hooks, context engineering, CLAUDE.md, CI/CD integration, and technical debt mitigation. 13 dedicated articles Connected to: Thread-Based Engineering, AI Technical Debt, Anthropic Agent SDK Key articles: - https://www.pixelmojo.io/blogs/claude-code-technical-debt-mitigation-guide - https://www.pixelmojo.io/blogs/claude-code-hooks-production-quality-ci-cd-patterns - https://www.pixelmojo.io/blogs/context-engineering-ai-coding-agents-beyond-claude-md - https://www.pixelmojo.io/blogs/we-audited-our-own-ai-architecture - https://www.pixelmojo.io/blogs/anthropic-agent-sdk-hooks-typescript-reference - https://www.pixelmojo.io/blogs/ghost-protocol-thread-based-multi-agent-engineering-ai-coding - https://www.pixelmojo.io/blogs/how-we-built-multi-channel-ai-sales-agent-one-tbe-session - https://www.pixelmojo.io/blogs/thread-based-agentic-experience-engineering-tbe-meets-axd - https://www.pixelmojo.io/blogs/llms-txt-static-vs-dynamic-implementation-guide - https://www.pixelmojo.io/blogs/slopsquatting-ai-supply-chain-attacks-defense-guide - https://www.pixelmojo.io/blogs/lakbay-ai-case-study-thread-based-engineering-in-production - https://www.pixelmojo.io/blogs/vibe-coding-technical-debt-crisis-2026-2027 - https://www.pixelmojo.io/blogs/complete-guide-ai-copilot-stack-multimodal-tools-developer-productivity **Anthropic Agent SDK** (Claude Agent SDK, Anthropic Claude Agent SDK, Claude Code Hooks SDK) The programmatic TypeScript surface for building agents on top of Claude. Covers the 12 hook events (PreToolUse, PostToolUse, UserPromptSubmit, Stop, SubagentStop, PreCompact, SessionStart, SessionEnd, Notification, PermissionRequest, SubagentStart, PostToolUseFailure), the HookCallback signature, hookSpecificOutput decisions (allow/deny/ask + updatedInput), and how programmatic hooks compare to declarative Claude Code settings.json hooks. 2 dedicated articles Connected to: Claude Code Development, Thread-Based Engineering Key articles: - https://www.pixelmojo.io/blogs/anthropic-agent-sdk-hooks-typescript-reference - https://www.pixelmojo.io/blogs/claude-code-hooks-production-quality-ci-cd-patterns **Design Psychology** (Behavioral Design, Cognitive Design Patterns) How cognitive biases, aesthetic-usability effects, and behavioral science shape design decisions that drive measurable business outcomes. 7 dedicated articles Connected to: Brand & Sales Design, AX Design Key articles: - https://www.pixelmojo.io/blogs/the-aesthetic-usability-effect-why-good-looking-designs-feel-easier-to-use - https://www.pixelmojo.io/blogs/why-beautiful-design-fails-to-sell - https://www.pixelmojo.io/blogs/why-your-design-teams-next-hire-should-think-like-a-computer-scientist - https://www.pixelmojo.io/blogs/thread-based-agentic-experience-engineering-tbe-meets-axd - https://www.pixelmojo.io/blogs/ax-metrics-measuring-agentic-experience-quality-beyond-task-completion - https://www.pixelmojo.io/blogs/agent-personality-voice-design-how-to-build-ai-coworkers-people-trust - https://www.pixelmojo.io/blogs/ax-design-trust-patterns-how-users-learn-to-rely-on-ai-coworkers **AI Code Ownership** (AI Agency Code Ownership, AI Vendor Lock-In Prevention, Build + Platform + Performance) Practice of structuring AI agency engagements so the customer owns the application source code, deployment infrastructure, and the right to modify or fork without vendor permission. Defines contract clauses (IP assignment, source code escrow, deployment access, knowledge transfer SLAs) that distinguish ownership engagements from typical lock-in consulting models. 1 dedicated article Connected to: AI Product Development, Thread-Based Engineering, Vector, Hive, Radar Key articles: - https://www.pixelmojo.io/blogs/ai-agency-code-ownership-without-vendor-lock-in **Growth Marketing** (AI Growth Marketing, Performance Marketing) Data-driven growth marketing strategies enhanced by AI: consumer behavior analysis, agency transformation, and AI-native marketing systems. 13 dedicated articles Connected to: Growth Marketing, Generative Engine Optimization Key articles: - https://www.pixelmojo.io/blogs/the-definitive-guide-to-growth-marketing-in-the-age-of-ai-strategies-frameworks-and-real-world-dominance - https://www.pixelmojo.io/blogs/growth-marketing-vs-traditional-marketing-the-complete-guide - https://www.pixelmojo.io/blogs/consumer-behavior-in-marketing-strategies-factors-technology-role-and-research-methods - https://www.pixelmojo.io/blogs/ai-native-design-agency-vs-traditional-agency-complete-guide - https://www.pixelmojo.io/blogs/budgeting-marketing-design-ai-automation-vs-traditional-agency-fees - https://www.pixelmojo.io/blogs/ai-visibility-evidence-standard - https://www.pixelmojo.io/blogs/before-you-hire-a-geo-agency - https://www.pixelmojo.io/blogs/ai-monitoring-vs-ai-technical-readiness - https://www.pixelmojo.io/blogs/gemini-25-youtube-ai-readable - https://www.pixelmojo.io/blogs/from-free-audit-to-ai-visibility-strategy - https://www.pixelmojo.io/blogs/what-is-ai-technical-readiness - https://www.pixelmojo.io/blogs/ai-product-development-philippines-cto-guide - https://www.pixelmojo.io/blogs/what-is-an-ai-native-agency-definition-guide ### Production Case Studies **Pixelmojo Brand System Case Study** Portfolio case study of the identity system built for the Pixelmojo product family. Shows the 64-unit four-cell grammar that generates the Radar, Vector, and Hive marks, the construction specs and usage rules, the color and type roles, the layout applications, and the voice. The reference guidelines themselves live at /brand. Case study: https://www.pixelmojo.io/projects/pixelmojo-brand-system Built with: Pixelmojo Brand System, Brand & Sales Design **Lakbay AI** AI-powered travel concierge for the Philippines. RAG-driven with pgvector embeddings across 18 destinations. Built with Thread-Based Engineering. Case study: https://www.pixelmojo.io/projects/lakbay-ai Built with: Thread-Based Engineering, AI Product Development **Mojo AI** Portfolio case study for a Figma creative workflow concept that explores controlled ad variations from one master template. The interactive demonstration uses synthetic data and does not claim a measured production output benchmark. Case study: https://www.pixelmojo.io/projects/mojo-ai Built with: AI Product Development **Resibo** Free offline receipt workspace that turns receipts into exportable expense records. Preview JPG, PNG, WEBP or PDF files, enter merchant, date, category, tax and line items, and export the reviewed records as CSV. Runs entirely in the browser with no accounts, no network requests and no storage, so files are cleared on refresh. This edition is manual entry by design and runs no AI extraction. Case study: https://www.pixelmojo.io/demo/resibo Built with: AI Product Development **SEO Intelligence Platform** Portfolio case study of a platform that reads traditional search performance and AI citation coverage in one view. Built on the Google Search Console MCP to monitor rankings, surface the gap between where a page ranks and where it is cited, and turn the widest gap into a content brief. Case study: https://www.pixelmojo.io/projects/seo-intelligence-platform Built with: AI Visibility Strategy, Generative Engine Optimization, AI Citation Tracker, Radar **Real Estate Earnings Tracker** Portfolio case study of a predictive analytics platform that turns property investment data into cash-flow forecasts. Models occupancy, operating cost and debt service per asset, and rolls them into portfolio-level coverage and cap-rate views. Case study: https://www.pixelmojo.io/projects/real-estate-earnings-tracker Built with: AI Product Development, Brand & Sales Design **Logistics Track & Trace System** Portfolio case study of an enterprise logistics platform that unified fragmented carrier and warehouse events into one shipment record. Normalizes events into a single state per shipment and surfaces exceptions before they become delays. Case study: https://www.pixelmojo.io/projects/logistics-track-trace-system Built with: AI Product Development, Thread-Based Engineering --- ### Full Entity Reference (All 61 Entities with Keywords and Relationships) #### Thread-Based Engineering - Type: Methodology - Description: Productivity and governance framework that treats each AI coding session as a measurable unit of work called a thread. Seven thread types (Base, P, L, C, F, B, Z) with mandatory human checkpoints at boundaries. - URL: https://www.pixelmojo.io/blogs/thread-based-engineering-scaling-ai-development - Also known as: TBE, Thread Engineering - Keywords: thread-based-engineering, ai-governance, code-quality, thread-types, z-threads - Related entities: Ghost Protocol (Methodology), AI Technical Debt (TopicCluster), Claude Code Development (TopicCluster), Lakbay AI (Project), AI Product Development (Service), Agentic Experience Engineering (Methodology), AI Code Ownership (TopicCluster) #### Ghost Protocol - Type: Methodology - Description: Multi-agent engineering framework built for GitHub Copilot. Gives Copilot 8 named specialist agents running 9 disciplined execution patterns. Dual routing assigns every task both a specialist (who) and a thread pattern (how). Includes Core Four quality framework, persistent agent memory, and auto-triggered ceremonies. One install command. - URL: https://www.pixelmojo.io/blogs/ghost-protocol-thread-based-multi-agent-engineering-ai-coding - Also known as: Ghost Protocol Framework, Multi-Agent Engineering Framework for GitHub Copilot - Keywords: ghost-protocol, dual-routing, core-four-framework, agent-charters, multi-agent-engineering - Related entities: Thread-Based Engineering (Methodology), Multi-Agent AI Systems (TopicCluster), AI Technical Debt (TopicCluster), Hive (Product) #### AX Design - Type: Methodology - Description: Design methodology for AI-as-coworker interfaces. Defines capability mapping, protocol stacks, and lifecycle patterns for agentic systems that act autonomously on behalf of users. - URL: https://www.pixelmojo.io/blogs/what-is-ax-design-complete-guide-agentic-experience-2026 - Also known as: Agentic Experience Design, Agentic UX, AX (Agentic Experience) - Keywords: agentic-ux-design, agentic-experience, ax-design, ai-coworker - Related entities: Design Psychology (TopicCluster), Multi-Agent AI Systems (TopicCluster), Hive (Product), Agentic Experience Engineering (Methodology) #### Agentic Experience Engineering - Type: Methodology - Description: Unified framework connecting Thread-Based Engineering (governance) with Agentic Experience Design (trust). Maps thread autonomy levels (B through Z) to supervision patterns (in-the-loop, on-the-loop, out-of-the-loop). Quality gates become trust signals. Thread lifecycles become conversation flows. - URL: https://www.pixelmojo.io/blogs/thread-based-agentic-experience-engineering-tbe-meets-axd - Also known as: Thread-Based Agentic Experience Engineering, TBE + AXD, Agentic Product Engineering - Keywords: agentic-experience-engineering, tbe-axd-framework, supervision-patterns, progressive-autonomy, shadow-to-steer-to-self - Related entities: Thread-Based Engineering (Methodology), AX Design (Methodology), Hive (Product), Vector (Product), Multi-Agent AI Systems (TopicCluster) #### AI Visibility - Type: TopicCluster - Description: Whether AI engines (ChatGPT, Claude, Perplexity, Gemini) can find, describe, and recommend a brand when buyers ask about its category. Splits into an answer stage, whether the brand appears and is cited, and a decision stage, whether the engine names it as the answer. - URL: https://www.pixelmojo.io/answers/what-is-ai-visibility - Also known as: AI Search Visibility, AI Brand Visibility - Keywords: ai-visibility, what-is-ai-visibility, ai-search-visibility, ai-brand-visibility, answer-stage, decision-stage-ai-visibility, ai-recommendations, ai-search - Related entities: Radar (Product), Generative Engine Optimization (Methodology), AI Visibility Tools (Product), AI Visibility Strategy (Service), Best AI Visibility Agencies (TopicCluster), AI Visibility Evidence Standard (Methodology) #### Generative Engine Optimization - Type: Methodology - Description: Framework for optimizing content to be cited by AI search engines (ChatGPT, Perplexity, Claude). Covers entity authority, structured data, llms.txt, speakable schema, AEO formatting (StatBlocks, KeyTakeaways), and citation patterns across generative engines. - URL: https://www.pixelmojo.io/blogs/geo-playbook-get-cited-chatgpt-perplexity-claude - Also known as: GEO, AI Search Optimization - Keywords: geo, generative-engine-optimization, ai-search, llms-txt, ai-citations, seo-vs-geo, aeo, answer-engine-optimization, speakable-schema, statblock - Related entities: AI Visibility (TopicCluster), Radar (Product), Growth Marketing (Service), AI Product Development (Service), AI Visibility Tools (Product) #### AI Visibility Evidence Standard - Type: Methodology - Description: Pixelmojo's proposed reporting standard for AI visibility results, version 1 (September 2026). Eight disclosures that let a reader judge whether a result is meaningful, comparable, and actionable: channel (provider API or consumer app, model, web search), prompt set, observations and uncertainty, definitions (mention, linked citation, recommendation), denominators, source evidence, comparability (method version and a dated change log), and outcomes kept separate from exposure. A proposal, not an industry standard or certification. - URL: https://www.pixelmojo.io/blogs/ai-visibility-evidence-standard - Also known as: Pixelmojo AI Visibility Evidence Standard, AI Visibility Evidence Standard v1 - Keywords: ai-visibility-evidence-standard, evidence-standard, measurement-standard, ai-visibility-report, ai-visibility-reporting - Related entities: AI Visibility (TopicCluster), Radar (Product), AI Citation Tracker (Product), AI Visibility Tools (Product) #### Vector - Type: Product - Description: 12-dimension AI lead qualification engine for B2B SaaS. Real-time conversation intelligence with emotional pattern detection, automated routing, and CRM integration. - URL: https://www.pixelmojo.io/vector - Also known as: Vector by Pixelmojo, Vector Lead Qualification - Keywords: lead-qualification, ai-sales-agent, vector, b2b-lead-scoring - Related entities: Hive (Product), Radar (Product), AI Product Development (Service), Multi-Agent AI Systems (TopicCluster), AI Code Ownership (TopicCluster) #### Hive - Type: Product - Description: Multi-agent orchestration platform where AI co-workers coordinate autonomously, share intelligence, and run operations. Powered by Vector. Enterprise verticals: logistics, insurance, HR, accounting. - URL: https://www.pixelmojo.io/hive - Also known as: Hive by Pixelmojo, Hive AI Co-workers - Keywords: multi-agent-platform, ai-coworkers, hive, agent-orchestration - Related entities: Vector (Product), Radar (Product), Multi-Agent AI Systems (TopicCluster), AX Design (Methodology), AI Product Development (Service), AI Code Ownership (TopicCluster) #### Radar - Type: Product - Description: Radar measures answer-stage AI visibility (whether ChatGPT, Claude, Gemini, and Perplexity mention and cite your brand, with suggested fixes) and is built toward decision-stage measurement: whether AI recommends you when buyers ask which option to choose (win-rate scoring is on the roadmap, not part of the current live score). Radar backs every score with a methodology you can defend: deterministic technical checks, fresh queries to the provider APIs of all four engines (consumer AI apps may answer differently), and stable judgment for the nuanced calls. It also surfaces the hallucinations and misattributions buyers see in production AI answers. Radar is complementary to AI monitoring platforms such as Profound, Ahrefs Brand Radar, and Otterly. Buying-question testing is not unique to Radar: platforms such as Profound and Ahrefs Brand Radar also track purchase-intent and recommendation prompts. Monitoring tracks AI answers over time, while a Radar audit pairs technical readiness checks with sampled AI answers and shows the evidence and a suggested fix behind each finding. Built for digital agencies whose clients ask "are we in ChatGPT?", B2B SaaS marketing teams losing organic traffic to AI search, and enterprise brand teams worried about uncontrolled AI descriptions. Radar orchestrates 13 tools in staged batches, running lightweight checks concurrently while isolating provider-intensive checks for reliable evidence collection (plus standalone YouTube Brand Monitor and AI Open Graph Auditor at /tools/*). Free tier (6 tools, technical readiness layer): AI bot crawl check, robots.txt analyzer, llms.txt validator, schema markup audit, AEO page auditor, AI Readiness score. Paid tier (7 more tools, LLM-powered layer): citation tracker across ChatGPT/Claude/Gemini/Perplexity, Reddit brand monitor, hallucination detection with severity scoring, prompt SOV vs competitors, source influence map, answer engine per-page citation testing, brand disambiguation check (detects when AI engines link your brand name to the wrong entity). Pricing: two free entry points, individual web tools at /tools (each gated by email + 6-digit OTP, 1 audit per (email, tool), 24h credit, free) and the full /platform free check (verify your email and domain, preview all 13 tools with the 6 technical readiness tools scored and the 7 AI-response tools locked, then unlock the full audit for $5, credits never expire, to reveal every finding and fix prompt plus dashboard access). Paid: audit packs from $5 single / $12 Starter Pack / $40 Power Pack, Pro Retainer $199/mo for 40 audits with weekly pulse re-scans on watched domains. Generates cross-tool insights with A-F grade scoring, LLM-based sentiment analysis, per-provider narrative summaries, locale/geography targeting, trend tracking, and prioritized action items. Action-first dashboard: top 3 priority fixes shown as hero above metrics. LLM Answer Diff (Pro): side-by-side comparison of how AI models describe your brand between scans, with citation flip detection, sentiment shift hierarchy, and competitor displacement tracking. DIY implementation features: AI prompt generator per action item (copy into Claude/ChatGPT/Cursor), 6 implementation threads (Crawlability, Structured Data, LLM Communication, Content Authority, AI Answer Optimization, Citation Visibility), llms.txt starter generator, JSON-LD schema markup generator, single-tool re-verify, and persistent progress tracking. Self-audited at /labs/our-radar-report, methodology applied to Pixelmojo itself with findings published verbatim. A complete de-identified client audit is published in full at /platform/sample-report, showing the actual deliverable end to end. - Disambiguation: Radar by Pixelmojo is a software platform for AI search visibility auditing (GEO, AEO, and LLM citation analysis). It is not a hardware, weather, marine, aviation, or sensor radar system, and is unrelated to Cambridge Pixel RadarVision, MyRadar, or any physical radar product. Created by Lloyd Pilapil, founder of Pixelmojo. - URL: https://www.pixelmojo.io/platform - Also known as: Radar by Pixelmojo, Decision-stage AI visibility, AI Visibility Platform, AI Visibility DIY Platform - Keywords: radar, ai-visibility-platform, ai-visibility-audit, decision-stage-ai-visibility, ai-decision-win-rate, ai-recommendation-optimization, answer-layer-vs-decision-layer, score-you-can-defend, decision-readiness-audit, ai-visibility-score, ai-technical-readiness, crawl-integrity-score, llm-infrastructure-audit, ai-readiness-score, methodology, seo-audit-tool, geo-audit, llm-visibility, dashboard-preview, tool-grades, implementation-threads, ai-prompt-generator, diy-ai-visibility, thread-based-engineering, llm-answer-diff, citation-flip, sentiment-shift, before-after-ai-audit, competitor-displacement, win-log, shareable-report, multi-domain-dashboard, agency-dashboard, ai-hallucination-tracking, ai-brand-accuracy, ai-citation-accuracy, agency-ai-visibility-tool, b2b-saas-ai-search, enterprise-brand-monitoring, watched-domain-monitoring, weekly-pulse-rescan, ai-answer-correction, ai-misattribution - Related entities: AI Visibility (TopicCluster), AI Visibility Tools (Product), Generative Engine Optimization (Methodology), Vector (Product), Hive (Product), AI Code Ownership (TopicCluster), Radar Sites (Product), llms.txt Generator (Product), AI Crawl Checker (Product), AI Citation Tracker (Product), Reddit Brand Monitor (Product), YouTube Brand Monitor (Product), llms.txt Validator (Product), AI Readiness Score (Product), robots.txt Analyzer for AI (Product), AEO Page Auditor (Product), Answer Engine Citation Tester (Product), Source Influence Map (Product), Prompt SOV Score (Product), Schema Completeness Audit (Product), Hallucination Detection (Product), Brand Disambiguation Check (Product), AI Open Graph Auditor (Product), Site Freshness Auditor (Product), AI Visibility Benchmarks by Industry (Anonymized) (Product), Radar AI Readiness Badge (Product), Radar Brand Index (Product), Pixelmojo Self-Audit (Product), Sample Radar Report (Product), Radar in Arabic (رادار بالعربية) (Product) #### Radar Sites - Type: Product - Description: Radar Sites is a capability of Radar, not a separate product: Pixelmojo's AI website builder for turning a business brief into a structured multi-page site, then refining it in a visual Studio with reviewable Director changes, draft readiness checks, HTML export, and approval-gated publishing. - URL: https://www.pixelmojo.io/radar-sites - Also known as: Radar Sites by Pixelmojo, Pixelmojo AI Website Builder - Keywords: radar-sites, ai-website-builder, visual-site-builder, multi-page-website-builder, reviewable-ai-editing, website-readiness-checks - Related entities: Radar (Product), Generative Engine Optimization (Methodology), Pixelmojo Brand System (TopicCluster) #### Radar in Arabic (رادار بالعربية) - Type: Product - Description: Arabic-language entry point to Radar's AI visibility audit for the Gulf market. Shows how ChatGPT, Claude, Gemini, and Perplexity describe a brand in Arabic and in English, and where the two pictures diverge. The audit can be scoped to Saudi Arabia, the UAE, or a regional GCC view — which changes the prompt library, entities, competitors, and local intent tested, NOT the geographic location the model is queried from. Prompts are written in Modern Standard Arabic and reviewed by native speakers rather than machine-translated. Delivered as a bilingual report with per-prompt evidence, citations, competitor comparison, and prioritized actions. - URL: https://www.pixelmojo.io/ar/radar - Also known as: Radar Arabic audit, AI visibility audit in Arabic, تدقيق حضور العلامة في الذكاء الاصطناعي, Radar Saudi Arabia, Radar UAE, Radar GCC - Keywords: radar-arabic, ai-visibility-arabic, arabic-ai-search, saudi-arabia-ai-visibility, uae-ai-visibility, gcc-ai-visibility, bilingual-ai-audit, arabic-llm-visibility - Related entities: Radar (Product), AI Visibility Tools (Product), Pixelmojo Brand System (TopicCluster) #### Pixelmojo Brand System - Type: TopicCluster - Description: The identity system that ties Radar, Vector, and Hive into one family. Not a logo but a rule for making logos: one geometric grammar (a 64-unit four-cell grid) generates every product mark, with pink #F90B8A reserved for the product's verb and a counter-shape answering it. Covers construction, clearspace, color, typography (Space Grotesk, Geist Sans, Geist Mono), lockups, misuse, and voice. - URL: https://www.pixelmojo.io/brand - Also known as: One grid, three verbs, Pixelmojo brand guidelines, Pixelmojo product family identity - Keywords: brand-system, brand-guidelines, design-system, product-family-identity, one-grid-three-verbs, logo-grammar, visual-identity - Related entities: Radar (Product), Vector (Product), Hive (Product), Brand & Sales Design (Service), Pixelmojo Brand System Case Study (Project) #### Consulting for Agencies - Type: Service - Description: Consulting and delivery support for agencies and consultancies that retain the client relationship while Pixelmojo executes an agreed website, application, AI visibility, audit, or monitoring scope behind the scenes. - URL: https://www.pixelmojo.io/consulting - Also known as: Consulting, Agency Partner Delivery, White-Label Website Delivery, White-Label AI Visibility Delivery - Keywords: consulting-for-agencies, agency-consulting, agency-partner-delivery, white-label-website-delivery, white-label-ai-visibility, agency-delivery-partner, consulting-partner - Related entities: AI Product Development (Service), AI Visibility Strategy (Service), Brand & Sales Design (Service), Growth Marketing (Service), Radar (Product) #### AI Product Development - Type: Service - Description: End-to-end AI product development: from architecture to deployment. LLM integration, RAG systems, multi-agent orchestration, and production AI infrastructure. - URL: https://www.pixelmojo.io/services/ai-product-development - Keywords: ai-product-development, llm-integration, rag-systems - Related entities: Thread-Based Engineering (Methodology), Vector (Product), Hive (Product), Ask Pixelmojo MCP Server (Service), Consulting for Agencies (Service), Multi-Agent AI Systems (TopicCluster), AI Code Ownership (TopicCluster), Mojo AI (Project), Resibo (Project), Real Estate Earnings Tracker (Project), Logistics Track & Trace System (Project) #### Ask Pixelmojo MCP Server - Type: Service - Description: Public, knowledge-only MCP service answering factual questions about Pixelmojo products, services, pricing, and methods with grounded answers, citations, relevance confidence, and fallback status. It cannot run audits or perform account, payment, or content actions. - URL: https://www.pixelmojo.io/api/mcp - Also known as: ask_pixelmojo, Pixelmojo Knowledge API - Keywords: ask-pixelmojo, mcp, knowledge-api, pixelmojo - Related entities: AI Product Development (Service), Radar (Product), Vector (Product), Hive (Product) #### Growth Marketing - Type: Service - Description: Marketing ops for B2B SaaS: content, lead scoring, email automation, and analytics. Pipeline generation without scaling headcount. - URL: https://www.pixelmojo.io/services/ai-powered-growth - Keywords: growth-marketing, pipeline-generation, lead-scoring, content-marketing, b2b-marketing - Related entities: Generative Engine Optimization (Methodology), Growth Marketing (TopicCluster) #### Brand & Sales Design - Type: Service - Description: Brand identity, design systems, pitch decks, and sales collateral shipped as one cohesive system for SaaS teams. - URL: https://www.pixelmojo.io/services/revenue-first-design - Keywords: brand-identity, design-systems, pitch-decks, sales-collateral, conversion-design - Related entities: Design Psychology (TopicCluster), Pixelmojo Brand System (TopicCluster) #### AI Visibility Strategy - Type: Service - Description: Done-for-you GEO, AEO, and LLM optimization service. Pixelmojo audits, fixes, or rebuilds your site to get cited across ChatGPT, Claude, Perplexity, and Gemini, powered by Radar. Choose a 6-week Visibility Sprint to optimize an existing site, or a full AI-native rebuild scoped per project. - URL: https://www.pixelmojo.io/services/ai-visibility-strategy - Also known as: GEO Consulting, AEO Optimization Service - Keywords: ai-visibility-strategy, geo-consulting, aeo-optimization, llm-optimization, ai-search-optimization, ai-citation-strategy - Related entities: AI Visibility (TopicCluster), Generative Engine Optimization (Methodology), Radar (Product), Vector (Product), Hive (Product), AI Visibility Tools (Product), Growth Marketing (Service), Consulting for Agencies (Service), Best AI Visibility Agencies (TopicCluster), SEO Intelligence Platform (Project) #### Best AI Visibility Agencies - Type: TopicCluster - Description: Comparison guide of agencies that help brands get cited by AI search engines through GEO, AEO, structured data, and entity authority building. Covers Pixelmojo, WebFX, Seer Interactive, iPullRank, NoGood, Siege Media, and Directive Consulting. - URL: https://www.pixelmojo.io/best-ai-visibility-agencies - Also known as: Best GEO Agencies, Best AEO Agencies, AI Visibility Agency Comparison - Keywords: best-ai-visibility-agencies, best-geo-agencies, best-aeo-agencies, ai-visibility-agency, geo-agency, ai-search-optimization-agency - Related entities: Generative Engine Optimization (Methodology), AI Visibility Strategy (Service), AI Visibility Tools (Product), Radar (Product) #### Radar vs Ahrefs Brand Radar - Type: TopicCluster - Description: Side by side comparison of Pixelmojo Radar and Ahrefs Brand Radar. Fresh API queries at audit time vs scheduled prompt tracking, hallucination detection, sentiment scoring, technical AI readiness audits, and pricing breakdown. - URL: https://www.pixelmojo.io/vs/brand-radar - Also known as: Brand Radar Alternative, Ahrefs Brand Radar Comparison, Radar Brand Radar Comparison - Keywords: ahrefs-brand-radar-alternative, brand-radar-vs-radar, ai-visibility-tool-comparison, cheaper-ahrefs-alternative, agency-ai-visibility-software, live-llm-tracking - Related entities: Radar (Product), AI Visibility Tools (Product), Generative Engine Optimization (Methodology) #### Radar vs Profound - Type: TopicCluster - Description: How Pixelmojo Radar and Profound fit together as complementary layers of AI visibility. Profound is an AI visibility monitoring platform that tracks share of voice across multiple AI engines over time; Radar pairs technical readiness checks with sampled AI answers and a suggested fix for each finding. Covers when to use which. - URL: https://www.pixelmojo.io/vs/profound - Also known as: Profound Alternative, Profound Comparison, Radar Profound Comparison - Keywords: profound-alternative, radar-vs-profound, profound-vs-radar, enterprise-ai-visibility-monitoring, ai-technical-readiness-vs-monitoring, profound-comparison - Related entities: Radar (Product), AI Visibility Tools (Product), Generative Engine Optimization (Methodology) #### AI Visibility Tools - Type: Product - Description: Radar orchestrates thirteen audits in staged batches inside the dashboard at /platform/app, running lightweight checks concurrently while isolating provider-intensive checks (AI Crawl Checker, AI Citation Tracker, Reddit Brand Monitor, llms.txt Validator, AI Readiness Score, robots.txt Analyzer, AEO Page Auditor, Answer Engine Citation Tester, Source Influence Map, Prompt SOV Score, Schema Completeness Audit, Hallucination Detection, Brand Disambiguation Check) plus standalone YouTube Brand Monitor, AI Open Graph Auditor, and Site Freshness Auditor. Ten of these audits are exposed as free single-use /tools/* pages with email + OTP verification, and two more (AEO Page Auditor and AI Citation Tracker) are paid-first /tools/* pages that preview the audit and open a $5 audit that runs inside the dashboard. Two additional /tools/* utilities ship beside them: Domain Comparison and the Embeddable Pixelmojo Badge. These tools form the AI Technical Readiness layer, which is complementary to AI monitoring platforms such as Profound and Ahrefs Brand Radar: monitoring tracks AI answers over time, while this layer checks whether AI systems can reach, read, and correctly identify a brand, with a suggested fix for each finding. This readiness layer feeds the decision-stage measurement Radar is building toward (a roadmap capability, not part of the current live score): the goal is not just being cited in AI answers but winning the recommendation. - URL: https://www.pixelmojo.io/tools - Also known as: Free AI SEO Tools, AI Optimization Tools - Keywords: ai-visibility, geo-tools, ai-seo-tools, free-tools - Related entities: AI Visibility (TopicCluster), Generative Engine Optimization (Methodology), Growth Marketing (Service), Radar (Product), Radar vs Ahrefs Brand Radar (TopicCluster), Radar vs Profound (TopicCluster), llms.txt Generator (Product), AI Crawl Checker (Product), AI Citation Tracker (Product), Reddit Brand Monitor (Product), YouTube Brand Monitor (Product), llms.txt Validator (Product), AI Readiness Score (Product), Free AI Visibility Checker (Product), robots.txt Analyzer for AI (Product), AEO Page Auditor (Product), Answer Engine Citation Tester (Product), Domain Comparison (Head-to-Head) (Product), Source Influence Map (Product), Prompt SOV Score (Product), Schema Completeness Audit (Product), Hallucination Detection (Product), Brand Disambiguation Check (Product), AI Open Graph Auditor (Product), Site Freshness Auditor (Product), AI Visibility Benchmarks by Industry (Anonymized) (Product), Radar AI Readiness Badge (Product), Radar Brand Index (Product), Pixelmojo Self-Audit (Product), Sample Radar Report (Product) #### AI Crawl Checker - Type: Product - Description: Check access policies for 17 crawlers, including OAI-SearchBot, Claude-SearchBot, and PerplexityBot. - URL: https://www.pixelmojo.io/tools/ai-crawl-checker - Also known as: AI Bot Checker, AI Crawl Audit - Keywords: ai-crawl-checker, bot-access, robots-txt, gptbot, claudebot, perplexitybot, crawl-audit - Related entities: AI Visibility Tools (Product), Generative Engine Optimization (Methodology) #### AI Citation Tracker - Type: Product - Description: Paid-first tool ($5 per audit) to check whether ChatGPT, Perplexity, Claude, Gemini, and Grok (report-only) mention or cite your brand. Tests brand recognition, competitive visibility, URL citations, and sentiment. The public page previews the audit and opens checkout; the run happens inside the Radar dashboard. - URL: https://www.pixelmojo.io/tools/ai-citation-tracker - Also known as: AI Brand Mention Checker, LLM Citation Checker - Keywords: ai-citation-tracker, citation-tracking, brand-mentions, chatgpt-citations, perplexity-citations, llm-visibility - Related entities: AI Visibility Tools (Product), Generative Engine Optimization (Methodology) #### Reddit Brand Monitor - Type: Product - Description: Free tool to find what people say about your brand on Reddit. Discovers real posts via Google search, detects AI-generated promotional content, and analyzes sentiment. - URL: https://www.pixelmojo.io/tools/reddit-brand-monitor - Also known as: Reddit LLM Seeding Detector, Reddit Mention Tracker - Keywords: reddit-brand-monitor, llm-seeding, reddit-mentions, astroturfing-detection, brand-monitoring - Related entities: AI Visibility Tools (Product), Generative Engine Optimization (Methodology) #### YouTube Brand Monitor - Type: Product - Description: Tracks brand mentions across YouTube videos. Scores five dimensions on a 100-point scale (volume, channel diversity, reach, sentiment, recency). Sentiment is transcript-grounded for the top five videos by views, a GPT-4o-mini pass over the actual spoken content catches sarcasm and late-video reversals that title-only analysis misses. Concentrated negative coverage (two or more negative videos from a single channel) is flagged as an actionable recommendation. Live YouTube Data API queries and live transcript fetches on every audit, no cached snapshots. - URL: https://www.pixelmojo.io/tools/youtube-brand-monitor - Also known as: YouTube Mention Tracker, YouTube Visibility Auditor, YouTube Coverage Checker - Keywords: youtube-brand-monitor, youtube-mentions, video-brand-tracking, creator-coverage, brand-monitoring, gemini-25, video-citations, youtube-ai-visibility, youtube-transcripts, transcript-sentiment, concentrated-negative-coverage, layer-2-audit - Related entities: AI Visibility Tools (Product), Reddit Brand Monitor (Product), Generative Engine Optimization (Methodology) #### llms.txt Validator - Type: Product - Description: Free tool to validate your llms.txt file against the emerging llmstxt.org specification. Analyzes structure, content sections, links, entity definitions, and use policy. - URL: https://www.pixelmojo.io/tools/llms-txt-validator - Also known as: llms.txt Checker, llms.txt Audit Tool - Keywords: llms-txt-validator, llms-txt, llmstxt, ai-discovery, llms-full-txt - Related entities: AI Visibility Tools (Product), Generative Engine Optimization (Methodology) #### AI Readiness Score - Type: Product - Description: Free tool that combines crawl access, structured data, llms.txt quality, content accessibility, and cross-signal readiness into a single unified 0-100 AI readiness score. - URL: https://www.pixelmojo.io/tools/ai-readiness-score - Also known as: AI Readiness Checker, AI Readiness Audit - Keywords: ai-readiness-score, ai-readiness, ai-audit, unified-score, readiness-assessment - Related entities: AI Visibility Tools (Product), Generative Engine Optimization (Methodology) #### Free AI Visibility Checker - Type: Product - Description: Free landing-page entry point to the AI Readiness Score. Tests whether ChatGPT, Claude, Perplexity, and Gemini can find, understand, and cite a brand, returning a 0-100 AI visibility score. Runs the AI Readiness Score engine rather than a separate scoring system. - URL: https://www.pixelmojo.io/tools/free-ai-visibility-checker - Also known as: AI Visibility Tool, AI Search Visibility Checker, LLM Visibility Checker - Keywords: free-ai-visibility-checker, ai-visibility-tool, ai-search-visibility-checker, llm-visibility-checker, ai-visibility-check - Related entities: AI Visibility Tools (Product), AI Readiness Score (Product), Generative Engine Optimization (Methodology) #### robots.txt Analyzer for AI - Type: Product - Description: Free tool to audit your robots.txt specifically for AI bot directives. Analyzes 16 bots across search, AI browse, AI train, and SEO categories with syntax validation and suggested improvements. - URL: https://www.pixelmojo.io/tools/robots-txt-analyzer - Also known as: AI robots.txt Checker, robots.txt Audit Tool - Keywords: robots-txt-analyzer, robots-txt, ai-bot-directives, gptbot, claudebot, perplexitybot, bot-rules - Related entities: AI Visibility Tools (Product), Generative Engine Optimization (Methodology) #### AEO Page Auditor - Type: Product - Description: Paid-first tool ($5 per audit) to score any web page for answer engine readiness. Analyzes speakable schema, answer-first content structure, structured data quality, data extractability, content freshness, and entity authority across 6 weighted categories. The public page previews the audit and opens checkout; the run happens inside the Radar dashboard. - URL: https://www.pixelmojo.io/tools/aeo-page-auditor - Also known as: AEO Audit Tool, Answer Engine Page Scanner - Keywords: aeo-page-auditor, aeo-audit, speakable-schema, answer-engine-optimization, page-level-aeo, structured-data-quality - Related entities: AI Visibility Tools (Product), Generative Engine Optimization (Methodology) #### Answer Engine Citation Tester - Type: Product - Description: Free tool to test if ChatGPT, Perplexity, Claude, Gemini, and Grok (report-only) cite or mention a specific page for a specific question. Identifies content alignment gaps and competitor pages being cited instead. - URL: https://www.pixelmojo.io/tools/answer-engine-tester - Also known as: Citation Tester, AI Page Citation Checker - Keywords: answer-engine-tester, page-citation, citation-testing, aeo-citation, ai-citation-checker, content-alignment - Related entities: AI Visibility Tools (Product), Generative Engine Optimization (Methodology), AI Citation Tracker (Product) #### Domain Comparison (Head-to-Head) - Type: Product - Description: Free head-to-head AI visibility comparison that audits two domains side-by-side across 5 free tools (crawl, robots.txt, llms.txt, readiness, schema). Produces a shareable scorecard URL with winner callout, per-tool breakdown, and embeddable SVG badge. Used for competitive intelligence, sales decks, and builder-in-public share-outs. - URL: https://www.pixelmojo.io/tools/compare - Also known as: AI Visibility Comparison, Domain vs Domain Audit, Competitor AI Audit - Keywords: domain-comparison, ai-visibility-comparison, head-to-head-audit, competitor-audit, side-by-side-scorecard, shareable-audit - Related entities: AI Visibility Tools (Product), Radar (Product), AI Readiness Score (Product), AEO Page Auditor (Product) #### llms.txt Generator - Type: Product - Description: Free, deterministic llms.txt generator. Reads the page title, meta description, Organization schema, products, and navigation, then assembles a structured llms.txt shaped to the standard Pixelmojo uses on its own site. No login, no LLM guesswork, no storage. Pairs with the llms.txt Validator and the Radar AI visibility platform. - URL: https://www.pixelmojo.io/tools/llms-txt-generator - Also known as: Free llms.txt Generator, llms.txt Builder, llms.txt Maker - Keywords: llms-txt-generator, llms-txt, generate-llms-txt, llms-txt-builder, free-llms-txt-tool, ai-visibility-tools - Related entities: AI Visibility Tools (Product), Radar (Product), Generative Engine Optimization (Methodology) #### AI Open Graph Auditor - Type: Product - Description: Free audit of Open Graph and Twitter Card metadata for AI shareability and citation discoverability. Checks og:title, og:description, og:image quality, twitter:card type, share image reachability (HTTPS + 5MB ceiling), canonical alignment with og:url, and JSON-LD coverage. Scores across 5 categories with grade A-F and prioritized fixes. Built for marketing teams shipping content that needs to render correctly in Slack, Discord, X, iMessage, and AI assistant share previews. - URL: https://www.pixelmojo.io/tools/open-graph-auditor - Also known as: OG Tag Auditor, Open Graph Checker, Social Card Auditor, Twitter Card Auditor - Keywords: open-graph, og-tags, opengraph-protocol, twitter-cards, social-cards, share-previews, ai-shareability, meta-tags, citation-discoverability - Related entities: AI Visibility Tools (Product), Radar (Product), AEO Page Auditor (Product), AI Crawl Checker (Product), Generative Engine Optimization (Methodology) #### Site Freshness Auditor - Type: Product - Description: Free site-wide audit of the five freshness signals AI search agents use when deciding what to monitor: sitemap lastmod tag distribution, RSS or Atom feed availability and recency, blog publishing cadence over the last 30/60/90 days, Article schema dateModified coverage across sampled URLs, and visible date stamps in rendered HTML. Built for the Information-Agent era of Google Search announced at I/O 2026 where continuous monitoring weights freshness signals heavily and stale sites get silently deprioritized. - URL: https://www.pixelmojo.io/tools/site-freshness-auditor - Also known as: Content Freshness Score, AI Agent Monitoring Readiness Audit, Sitemap Freshness Checker - Keywords: content-freshness, sitemap-lastmod, rss-feeds, publishing-cadence, date-modified, article-schema, google-information-agents, ai-monitoring, agentic-search - Related entities: AI Visibility Tools (Product), Radar (Product), AEO Page Auditor (Product), AI Open Graph Auditor (Product), Generative Engine Optimization (Methodology) #### Radar AI Readiness Badge - Type: Product - Description: Free embeddable SVG badge that shows a domain’s AI Readiness score. shields.io-style pill format auto-updates when the underlying audit is re-run, designed for GitHub READMEs, docs sites, trust pages, blog posts, and email signatures. Every embed functions as a passive backlink and brand impression, creating a compounding discovery loop for the Radar platform. - URL: https://www.pixelmojo.io/tools/badge - Also known as: AI Readiness Badge, Radar Scorecard Badge, Embeddable AI Visibility Badge - Keywords: ai-readiness-badge, embeddable-scorecard, ai-visibility-badge, github-readme-badge, shields-io-style-badge, backlink-badge, trust-signal-badge - Related entities: AI Visibility Tools (Product), Radar (Product), AI Readiness Score (Product), Domain Comparison (Head-to-Head) (Product) #### Source Influence Map - Type: Product - Description: Radar tool that identifies the top URLs and domains AI models reference when discussing a brand or category. Shows which sources are shaping AI narratives, providing an editorial hit list for content strategy. - URL: https://www.pixelmojo.io/platform - Also known as: Source Map, AI Source Tracker - Keywords: source-influence, ai-source-tracking, editorial-strategy, citation-sources - Related entities: AI Visibility Tools (Product), Generative Engine Optimization (Methodology), Radar (Product) #### Prompt SOV Score - Type: Product - Description: Radar tool that measures brand share of voice in AI-generated recommendations. Runs industry prompts across ChatGPT, Claude, Perplexity, and Gemini to calculate position-weighted competitive rankings. - URL: https://www.pixelmojo.io/platform - Also known as: Share of Voice Score, AI SOV Tracker - Keywords: share-of-voice, ai-sov, competitive-ranking, brand-visibility, prompt-sov - Related entities: AI Visibility Tools (Product), Generative Engine Optimization (Methodology), Radar (Product), AI Citation Tracker (Product) #### Schema Completeness Audit - Type: Product - Description: Radar tool that validates JSON-LD structured data across 10 Schema.org types: Organization, Article, FAQ, HowTo, Speakable, BreadcrumbList, Product, LocalBusiness, WebSite, and SoftwareApplication. Checks field completeness, speakable schema presence, and coverage across multiple pages. - URL: https://www.pixelmojo.io/platform - Also known as: Schema Audit, JSON-LD Validator - Keywords: schema-audit, json-ld-validation, structured-data-audit, speakable-schema - Related entities: AI Visibility Tools (Product), Generative Engine Optimization (Methodology), Radar (Product) #### Hallucination Detection - Type: Product - Description: Radar tool that detects factual inaccuracies in AI-generated claims about a brand. Extracts ground truth from the brand website, queries AI providers, and compares for wrong pricing, products, founding year, or descriptions. Flags inaccuracies by severity. - URL: https://www.pixelmojo.io/platform - Also known as: AI Hallucination Checker, Brand Accuracy Checker - Keywords: hallucination-detection, ai-accuracy, brand-safety, fact-checking, ai-hallucination - Related entities: AI Visibility Tools (Product), Generative Engine Optimization (Methodology), Radar (Product), AI Citation Tracker (Product) #### Brand Disambiguation Check - Type: Product - Description: Paid-exclusive Radar tool that checks whether AI engines link your brand to the correct real-world entity or confuse it with a same-named company, person, or product. Extracts ground truth from your site and llms.txt, queries ChatGPT, Claude, Gemini, and Perplexity, and flags named-entity-disambiguation failures by severity. Runs inside the Radar dashboard for paid users, with a public explainer (labeled example, no free run) at /tools/brand-disambiguation. - URL: https://www.pixelmojo.io/tools/brand-disambiguation - Also known as: AI Entity Linking Checker, Entity Collision Check - Keywords: brand-disambiguation, entity-linking, named-entity-disambiguation, ai-brand-identity, same-name-confusion - Related entities: AI Visibility Tools (Product), Generative Engine Optimization (Methodology), Radar (Product), Hallucination Detection (Product) #### AI Visibility Benchmarks by Industry (Anonymized) - Type: Product - Description: Anonymized score distributions by industry, auto-refreshed hourly via Next.js ISR (stale-while-revalidate) from real Radar platform audits. Public pages show only rank, industry, score, and grade. The page distinguishes raw audited domains (every domain that has run a Radar audit) from surfaced domains (those in industries meeting the 3-domain threshold). Recently-audited domains in micro-categories sit invisible until peers join them. Domain and brand identifiers are never fetched or rendered. Users benchmark where their domain would rank against industry peers without exposing any site identity, same approach as Glassdoor salary bands. - URL: https://www.pixelmojo.io/labs/leaderboards - Also known as: AI Readiness Benchmarks, Industry AI Visibility Distribution, Anonymized AI Search Benchmarks - Keywords: ai-visibility-benchmarks, ai-readiness-distribution, industry-benchmarks, anonymized-rankings, score-distribution, peer-comparison - Related entities: Radar (Product), AI Readiness Score (Product), AI Visibility Tools (Product), Generative Engine Optimization (Methodology) #### Radar Brand Index - Type: Product - Description: Curated public reference index of 50 named brands across SaaS, E-commerce, Fintech, Healthcare, and Media. Each score is Radar's AI Readiness Score for the brand's site: AI bot access, structured data, llms.txt, content accessibility and cross-signal consistency. The score comes from technical checks of the site, not from AI answers, so it shows technical readiness, not whether AI answers cite or recommend the brand. Brands are re-scanned on a rolling schedule, and each score shows the date of its scan. Methodology is published on /platform/methodology. Brands behind hard paywalls or aggressive anti-bot defenses are explicitly flagged as "Audit Blocked" rather than scored zero, distinguishing sites Radar could not evaluate from poorly-optimized ones. Free to browse, anonymous, no signup. The index is part of Radar, surfaced as a Pixelmojo Labs research surface rather than inside the paid /platform dashboard. - URL: https://www.pixelmojo.io/labs/brand-index - Also known as: Pixelmojo Brand Index, Transparent AI Visibility Reference Index, AI Visibility Brand Index, Live Brand AI Readiness Index - Keywords: brand-index, ai-visibility-reference, curated-brand-benchmark, live-brand-audits, transparent-methodology, category-leaderboards, audit-blocked-paywall, brand-ai-readiness-score, public-brand-index - Related entities: Radar (Product), AI Readiness Score (Product), AI Visibility Benchmarks by Industry (Anonymized) (Product), AI Visibility Tools (Product), AEO Page Auditor (Product), Generative Engine Optimization (Methodology), Pixelmojo Self-Audit (Product) #### Pixelmojo Self-Audit - Type: Product - Description: Pixelmojo's own AI visibility scorecard: the latest full Radar audit of pixelmojo.io, published verbatim. Same 13-tool methodology applied to ourselves: overall unified score and grade, per-tool breakdown, per-LLM citation coverage (how often each provider's answers cited a pixelmojo.io URL), share-of-voice rank within the audited category, and any hallucination flags surfaced by the audit (verbatim quotes of what AI providers tell users vs. what is actually true). Server-side ISR every 6 hours picks up each new radar_audit_runs row for pixelmojo.io. Acts as a transparent dogfood proof for Radar customers: if our score drops, the page reflects that; if new hallucinations surface, they appear with the offending AI provider named. - URL: https://www.pixelmojo.io/labs/our-radar-report - Also known as: Our Radar Report, Pixelmojo AI Visibility Self-Audit, Radar Dogfood Report - Keywords: pixelmojo-self-audit, radar-dogfood, our-radar-report, pixelmojo-ai-visibility, transparent-self-audit, radar-self-audit, live-self-audit - Related entities: Radar (Product), Radar Brand Index (Product), AI Readiness Score (Product), AI Visibility Tools (Product), AEO Page Auditor (Product) #### Sample Radar Report - Type: Product - Description: A complete 13-tool Radar AI visibility audit published in full, exactly as the client received it, with the client de-identified. The subject is a boutique travel agency that scored 33 out of 100 (grade D). Contains the executive summary, all 13 tool scores with grades, a per-engine breakdown of what ChatGPT, Claude, Perplexity, Gemini, and Grok returned when asked about the company, query coverage by type, a competitive AI share-of-voice benchmark, content citation analysis, five key findings each with evidence and implication, an eight-item prioritized fix list with impact/effort/priority, and a re-measurement plan. Headline findings: three of four engines described a different same-named business (Brand Disambiguation scored 20), structured data and llms.txt both scored 0, and the company appeared 0 times across 8 competitive buying-stage queries at rank 119 of 118 brands found. Answers "what does a Radar report actually contain?" without a signup or purchase. - Disambiguation: A fixed historical client deliverable, de-identified. Distinct from /labs/our-radar-report (the latest self-audit of pixelmojo.io) and /labs/brand-index (50 named brands audited publicly). - URL: https://www.pixelmojo.io/platform/sample-report - Also known as: Sample AI Visibility Report, Example Radar Audit, De-Identified Radar Client Audit - Keywords: radar-sample-report, sample-ai-visibility-report, example-radar-audit, ai-visibility-report-example, what-is-in-a-radar-report, ai-audit-deliverable, de-identified-client-audit - Related entities: Radar (Product), Pixelmojo Self-Audit (Product), Radar Brand Index (Product), AI Readiness Score (Product), Brand Disambiguation Check (Product) #### Pixelmojo Brand System Case Study - Type: Project - Description: Portfolio case study of the identity system built for the Pixelmojo product family. Shows the 64-unit four-cell grammar that generates the Radar, Vector, and Hive marks, the construction specs and usage rules, the color and type roles, the layout applications, and the voice. The reference guidelines themselves live at /brand. - URL: https://www.pixelmojo.io/projects/pixelmojo-brand-system - Also known as: One Grid, Three Verbs, Pixelmojo product family identity case study - Keywords: pixelmojo-brand-system, brand-system-case-study, product-family-identity, logo-grammar, design-system-case-study - Related entities: Pixelmojo Brand System (TopicCluster), Brand & Sales Design (Service) #### Lakbay AI - Type: Project - Description: AI-powered travel concierge for the Philippines. RAG-driven with pgvector embeddings across 18 destinations. Built with Thread-Based Engineering. - URL: https://www.pixelmojo.io/projects/lakbay-ai - Also known as: Lakbay AI Travel Concierge - Keywords: lakbay-ai, ai-travel, rag-travel-concierge - Related entities: Thread-Based Engineering (Methodology), AI Product Development (Service) #### Mojo AI - Type: Project - Description: Portfolio case study for a Figma creative workflow concept that explores controlled ad variations from one master template. The interactive demonstration uses synthetic data and does not claim a measured production output benchmark. - URL: https://www.pixelmojo.io/projects/mojo-ai - Also known as: Mojo AI Figma Plugin - Keywords: mojo-ai, figma-plugin, ai-creative-automation - Related entities: AI Product Development (Service) #### Resibo - Type: Project - Description: Free offline receipt workspace that turns receipts into exportable expense records. Preview JPG, PNG, WEBP or PDF files, enter merchant, date, category, tax and line items, and export the reviewed records as CSV. Runs entirely in the browser with no accounts, no network requests and no storage, so files are cleared on refresh. This edition is manual entry by design and runs no AI extraction. - URL: https://www.pixelmojo.io/demo/resibo - Also known as: Resibo Receipt Workspace, Resibo by Pixelmojo - Keywords: resibo, receipt-to-csv, expense-tracker, offline-receipt-workspace - Related entities: AI Product Development (Service) #### SEO Intelligence Platform - Type: Project - Description: Portfolio case study of a platform that reads traditional search performance and AI citation coverage in one view. Built on the Google Search Console MCP to monitor rankings, surface the gap between where a page ranks and where it is cited, and turn the widest gap into a content brief. - URL: https://www.pixelmojo.io/projects/seo-intelligence-platform - Also known as: SEO + GEO Intelligence Platform - Keywords: seo-intelligence-platform, seo-geo-dashboard, ai-citation-coverage, search-console-mcp - Related entities: AI Visibility Strategy (Service), Generative Engine Optimization (Methodology), AI Citation Tracker (Product), Radar (Product) #### Real Estate Earnings Tracker - Type: Project - Description: Portfolio case study of a predictive analytics platform that turns property investment data into cash-flow forecasts. Models occupancy, operating cost and debt service per asset, and rolls them into portfolio-level coverage and cap-rate views. - URL: https://www.pixelmojo.io/projects/real-estate-earnings-tracker - Also known as: Property Earnings Tracker - Keywords: real-estate-earnings-tracker, property-analytics, cash-flow-forecasting, portfolio-underwriting - Related entities: AI Product Development (Service), Brand & Sales Design (Service) #### Logistics Track & Trace System - Type: Project - Description: Portfolio case study of an enterprise logistics platform that unified fragmented carrier and warehouse events into one shipment record. Normalizes events into a single state per shipment and surfaces exceptions before they become delays. - URL: https://www.pixelmojo.io/projects/logistics-track-trace-system - Also known as: Shipment Control Tower - Keywords: logistics-track-trace-system, shipment-visibility, supply-chain-exceptions, control-tower - Related entities: AI Product Development (Service), Thread-Based Engineering (Methodology) #### Multi-Agent AI Systems - Type: TopicCluster - Description: Architecture patterns for systems where multiple AI agents coordinate, share intelligence, and act autonomously. Covers orchestration, handoffs, and enterprise deployment. - URL: https://www.pixelmojo.io/blogs/multi-agent-ai-systems-explained-when-one-ai-isnt-enough - Also known as: Multi-Agent Orchestration, Agentic AI - Keywords: multi-agent, agentic-ai, agent-orchestration, ai-coworkers - Related entities: Hive (Product), AX Design (Methodology), AI Product Development (Service) #### AI Technical Debt - Type: TopicCluster - Description: The growing problem of technical debt from AI-generated code: security flaws in 45% of AI code tests, an 86% XSS failure rate, and 66% of developers frustrated by "almost right" output. Causes, measurement, and prevention strategies. - URL: https://www.pixelmojo.io/blogs/vibe-coding-technical-debt-crisis-2026-2027 - Also known as: Vibe Coding Debt, AI Code Quality Crisis - Keywords: ai-technical-debt, vibe-coding, code-quality, code-churn - Related entities: Thread-Based Engineering (Methodology), Claude Code Development (TopicCluster) #### Claude Code Development - Type: TopicCluster - Description: Patterns and workflows for production AI-assisted development using Claude Code: hooks, context engineering, CLAUDE.md, CI/CD integration, and technical debt mitigation. - URL: https://www.pixelmojo.io/blogs/claude-code-technical-debt-mitigation-guide - Also known as: Claude Code Workflows, AI-Assisted Development - Keywords: claude-code, claude-md, context-engineering, ai-coding, hooks - Related entities: Thread-Based Engineering (Methodology), AI Technical Debt (TopicCluster), Anthropic Agent SDK (TopicCluster) #### Anthropic Agent SDK - Type: TopicCluster - Description: The programmatic TypeScript surface for building agents on top of Claude. Covers the 12 hook events (PreToolUse, PostToolUse, UserPromptSubmit, Stop, SubagentStop, PreCompact, SessionStart, SessionEnd, Notification, PermissionRequest, SubagentStart, PostToolUseFailure), the HookCallback signature, hookSpecificOutput decisions (allow/deny/ask + updatedInput), and how programmatic hooks compare to declarative Claude Code settings.json hooks. - URL: https://www.pixelmojo.io/blogs/anthropic-agent-sdk-hooks-typescript-reference - Also known as: Claude Agent SDK, Anthropic Claude Agent SDK, Claude Code Hooks SDK - Keywords: anthropic-agent-sdk, claude-agent-sdk, typescript-hooks, claude-code-hooks, pretooluse, posttooluse, subagentstop, userpromptsubmit, hook-callback, hookspecificoutput - Related entities: Claude Code Development (TopicCluster), Thread-Based Engineering (Methodology) #### Design Psychology - Type: TopicCluster - Description: How cognitive biases, aesthetic-usability effects, and behavioral science shape design decisions that drive measurable business outcomes. - URL: https://www.pixelmojo.io/blogs/the-aesthetic-usability-effect-why-good-looking-designs-feel-easier-to-use - Also known as: Behavioral Design, Cognitive Design Patterns - Keywords: design-psychology, aesthetic-usability, behavioral-design, ux-psychology - Related entities: Brand & Sales Design (Service), AX Design (Methodology) #### AI Code Ownership - Type: TopicCluster - Description: Practice of structuring AI agency engagements so the customer owns the application source code, deployment infrastructure, and the right to modify or fork without vendor permission. Defines contract clauses (IP assignment, source code escrow, deployment access, knowledge transfer SLAs) that distinguish ownership engagements from typical lock-in consulting models. - URL: https://www.pixelmojo.io/blogs/ai-agency-code-ownership-without-vendor-lock-in - Also known as: AI Agency Code Ownership, AI Vendor Lock-In Prevention, Build + Platform + Performance - Keywords: ai-code-ownership, ai-vendor-lock-in, ai-agency-contract, build-platform-performance, own-code-ai, code-escrow, ip-assignment - Related entities: AI Product Development (Service), Thread-Based Engineering (Methodology), Vector (Product), Hive (Product), Radar (Product) #### Growth Marketing - Type: TopicCluster - Description: Data-driven growth marketing strategies enhanced by AI: consumer behavior analysis, agency transformation, and AI-native marketing systems. - URL: https://www.pixelmojo.io/blogs/the-definitive-guide-to-growth-marketing-in-the-age-of-ai-strategies-frameworks-and-real-world-dominance - Also known as: AI Growth Marketing, Performance Marketing - Keywords: growth-marketing, ai-marketing, agency, b2b-marketing - Related entities: Growth Marketing (Service), Generative Engine Optimization (Methodology) --- ## Research ### State of AI Visibility 2026 Live benchmark of Radar platform audits: overall scores, grades and industry averages. Each domain counts once, from its latest audit. An audit averages every check it completed: the six technical readiness checks, plus the live AI answer checks in full audits. Industries appear only with 3 or more labelled domains. The technical checks show readiness, not whether AI engines cite a site. Live figures: https://www.pixelmojo.io/labs/state-of-ai-visibility-2026 and https://www.pixelmojo.io/labs/state-of-ai-visibility-2026/data.json URL: https://www.pixelmojo.io/labs/state-of-ai-visibility-2026 Published: April 2026 (live dataset) Type: Research Report ### AI Visibility Benchmarks (Anonymized, Auto-Refreshed Hourly) Anonymized score distributions by industry, pulled live from the Radar platform audit database and refreshed hourly via Next.js ISR (stale-while-revalidate). The page distinguishes raw audited domains (every domain that has run a Radar audit) from surfaced domains (those in industries meeting the 3-domain threshold for public listing). Recently-audited domains in micro-categories sit invisible until peers join them. Privacy architecture: The public RPC (get_leaderboard) returns only rank, category, unified_score, unified_grade, and last_audited. Domain and brand columns are never fetched or rendered on public pages. Delivers the same benchmarking value as Glassdoor salary bands: aggregate signal that helps users benchmark without exposing individual identities. Methodology: Uses the latest audit per unique domain (so stale scores roll off as users re-audit). Unified 0-100 AI readiness score is computed by averaging 6 content-surface tools: crawl accessibility, robots.txt configuration, llms.txt implementation, AI readiness composite, schema markup quality, and answer engine optimization. Surface rule: An industry publishes only when 3+ unique domains are audited in that category. Prevents micro-categories from becoming de-facto identifiers (same threshold enforced on both the categories RPC and the ranked rows RPC). Known limitation: Scores reflect the audited URL only. Multi-subdomain brands (blog.google, developers.google.com, etc.) may under-score at the homepage level because their AI surface lives on subdomains. - Index URL: https://www.pixelmojo.io/labs/leaderboards - Per-category URLs: https://www.pixelmojo.io/labs/leaderboards/[category-slug] - Refresh: hourly (Next.js ISR, stale-while-revalidate) - Type: Anonymized industry benchmarks - Published: April 2026 (ongoing) ### Brand Index, 50 Curated Named Brands, AI Readiness Scores, Transparent Methodology Curated public reference index of 50 named brands across 5 industries (SaaS, E-commerce, Fintech, Healthcare, Media, 10 each). Distinct from /labs/leaderboards (anonymized aggregate stats) in that the Brand Index publishes specific brand identifiers and per-brand detail pages. Each score is Radar's AI Readiness Score for the brand's site: AI bot access, structured data, llms.txt, content accessibility and cross-signal consistency. The score comes from technical checks of the site, not from AI answers, so it shows technical readiness, not whether AI answers cite or recommend the brand. A full Radar audit adds the live checks of what ChatGPT, Claude, Gemini and Perplexity say about a brand, including citation tracking, hallucination detection and prompt share of voice. Methodology published at /platform/methodology. Differentiator vs commercial AI-visibility indexes (Parse, etc.): transparent published methodology not opaque "we measure visibility" claims, "Audit Blocked" honest treatment for paywalled or anti-bot-blocked sites instead of forcing a meaningless 0 score. Smaller scale (50 vs hundreds of thousands) but designed as an editorial reference, not a mass-search SaaS. Score: Radar's AI Readiness Score, a technical check of each brand's own site. The State of AI Visibility 2026 report uses a different score: the overall score of each Radar platform audit. Categories with 10 brands each: - SaaS: Notion, Linear, Figma, Webflow, Slack, Asana, Airtable, Loom, Calendly, Zapier - E-commerce: Shopify, Glossier, Allbirds, Patagonia, Warby Parker, Casper, Bombas, Everlane, Away, Outdoor Voices - Fintech: Stripe, Plaid, Wise, Revolut, Chime, Brex, Ramp, Mercury, Klarna, Affirm - Healthcare: Headspace, Calm, Hims, Hers, Ro, One Medical, Teladoc, Oscar Health, BetterUp, Forward - Media: Substack, NYT, The Atlantic, Vox, The Verge, TechCrunch, Wired, Quartz, The Information, Stratechery Consent / removal: brands can request removal at any time via founders@pixelmojo.io. Removal is permanent and respected on every future catalog refresh. - Index URL: https://www.pixelmojo.io/labs/brand-index - Per-brand URLs: https://www.pixelmojo.io/labs/brand-index/[brand-slug] - Refresh: Brands are re-scanned on a rolling schedule, and each score shows the date of its scan. - Cost: $0 to readers, ~$15/mo OpenAI cost to Pixelmojo - Type: Curated reference index with named brands - Methodology: https://www.pixelmojo.io/platform/methodology - Launched: May 2026 (ongoing) ### What Radar Caught About Us, Pixelmojo Self-Audit The Pixelmojo team runs Radar against pixelmojo.io and publishes the latest audit's findings at /labs/our-radar-report. The page is reframed as a demonstration of Radar's value, not a Pixelmojo scorecard: the headline finding is the hallucinations Radar found in the provider API answers it collected about Pixelmojo, quoted verbatim (what the AI answer said vs. what is actually true). Subsequent sections cover the technical strengths the audit confirms (grade-A tools), the latest audit's top recommended fixes, the overall score with context, the per-tool breakdown, and per-LLM citation coverage. Why this page exists: Brand Index scores 50 named brands publicly with Radar's AI Readiness Score. This page applies the full Radar audit to Pixelmojo itself. Publishing only flattering numbers would invalidate the methodology. Publishing what it actually finds (including hallucinations and AEO gaps) is the proof. Same JSON shape and scoring formula as every customer audit. Sales/positioning angle: Radar checks whether what AI answers say about a brand is accurate, then surfaces the corrections needed. The hallucination findings on this page are the value proposition, not a concession. Companion to /labs/brand-index (50 brands, anonymized aggregates at /labs/leaderboards). Differs from those by being a single-brand deep dive focused on hallucination detection and AEO gap identification. - URL: https://www.pixelmojo.io/labs/our-radar-report - Refresh: shows the latest Radar audit of pixelmojo.io (server-side ISR every 6 hours picks up each new `radar_audit_runs` row) - Methodology: https://www.pixelmojo.io/platform/methodology - Type: Public self-audit / dogfood proof - Launched: May 2026 ### Sample Radar Report, Full De-Identified Client Audit A complete 13-tool Radar audit published in full at /platform/sample-report, exactly as the client received it, with the client de-identified. The subject is a boutique travel agency that scored 33 out of 100 (grade D). Their brand name, domain, the same-name businesses they collide with, the individuals named in engine responses, the audit run id, and their specific destination specialties are all removed. Every score, count, and finding is unedited. What the page contains, in the order the report presents it: an executive summary, the overall score with a plain-English reading, all 13 tool scores with grades and what each measures, a per-engine breakdown of what ChatGPT, Claude, Perplexity, Gemini, and Grok actually returned when asked about the company, query coverage by type, a competitive AI share-of-voice benchmark against booking.com/kayak/expedia, content citation analysis, five key findings each with evidence and implication, an eight-item prioritized fix list with impact/effort/priority, and a re-measurement plan with leading indicators. Headline findings from this audit, useful as a worked example of what Radar detects: three of four engines described a different same-named business when asked about the company (Brand Disambiguation scored 20); structured data and llms.txt both scored 0, leaving engines nothing authoritative to verify against; the company appeared 0 times across 8 competitive buying-stage queries, ranking 119 of 118 brands found. The technical foundation was sound (full bot access, valid robots.txt, server-rendered), so the prescribed fixes are markup and content work, not re-platforming. Why this page exists: /labs/our-radar-report shows Radar pointed at Pixelmojo, and /labs/brand-index shows it pointed at 50 known brands. This page shows the actual client deliverable, which neither of those does. Answers the question "what does a Radar report actually contain?" without requiring a signup or a purchase. - URL: https://www.pixelmojo.io/platform/sample-report - Refresh: static (a fixed historical audit, not re-run) - Methodology: https://www.pixelmojo.io/platform/methodology - Type: Sample deliverable / de-identified client audit - Subject scored: 33/100, grade D - Published: July 2026 --- ## Video Pixelmojo publishes short videos about Radar and the company on its [YouTube channel](https://www.youtube.com/@pixelmojohq). Each long-form video is below with its transcript, and each has a page on the site: https://www.pixelmojo.io/videos. A Short is a vertical cut of a long-form video with the same narration, captions or sound-cue track. Scout is the guide character in the Radar videos. ### A Closer Look at Pixelmojo: Radar, Vector and Hive - Watch: https://www.youtube.com/watch?v=iYpV-G7rerA - Page with transcript: https://www.pixelmojo.io/videos/a-closer-look-at-pixelmojo - Length: 2:25 - Related page: https://www.pixelmojo.io/about - About: Lloyd Pilapil, founder of Pixelmojo, and Scout, the guide to Radar, take a closer look at Radar, Radar Sites (a visual website builder in development), Vector and Hive. - Note: This is an animated film. The AI answer, website and lead scenes are illustrative examples, not a real client result. Transcript: When someone asks AI who to choose, does it understand your business? Lloyd, over here! I'm Lloyd, founder of Pixelmojo. Meet Scout, our guide to Radar. I found something. Come look. This says you only work with big companies. But your website says you help smaller teams too. That's quite a difference. Radar helps you inspect AI answers and the evidence behind them. So we fixed the website and we're done? We make a useful change, then check again. New evidence tells us what to do next. Right, no guessing. And we're building Radar Sites, a visual website builder. Let me get this side. New leads? Send them all to sales. First, find the fit. Vector qualifies incoming leads and routes the next step around your sales process. This one needs a closer look. Hive helps AI co-workers share context and hand work to the right place. Even when a person needs to take over? Especially then. That's Pixelmojo. AI products, visibility, brand and growth. With Vector and Hive, you own the custom application. We maintain the intelligence. But I keep the magnifying glass. Deal. Welcome to Pixelmojo. One more thing. A closer look? Always. ### Meet Pixelmojo: AI Products for Real Business - Watch: https://www.youtube.com/watch?v=VJ-rZOCSdnk - Page with transcript: https://www.pixelmojo.io/videos/meet-pixelmojo - Length: 1:05 - Related page: https://www.pixelmojo.io/about - About: Lloyd Pilapil, founder of Pixelmojo, introduces Radar, Radar Sites, Vector and Hive in one minute. - Note: The introduction uses AI-generated video. The report on screen is an excerpt from the public Radar sample report with client details removed; product scenes are illustrative. Transcript: I'm Lloyd, founder of Pixelmojo. We build AI products for discovery, lead qualification, and business operations. Radar is where many teams start. It helps you inspect how AI describes your business, examine the evidence, and decide what to improve next. Your team makes the changes, then checks what happened. We're also developing Radar Sites, a visual builder for websites. Vector qualifies and routes incoming leads around your sales process, giving your team a clearer next step. Hive coordinates specialized AI co-workers so they can share context, hand off work, and bring in people. With Vector and Hive, you own the custom application. We maintain the intelligence. Welcome to Pixelmojo. ### Can AI Tell Your Client Apart? A Real AI Visibility Finding - Watch: https://www.youtube.com/watch?v=6VWeG1Xx4rs - Page with transcript: https://www.pixelmojo.io/videos/can-ai-tell-your-client-apart - Length: 1:24 - Related page: https://www.pixelmojo.io/platform/sample-report - Short version (1:24): [Same Name, Different Business: Can AI Tell Your Client Apart? #Shorts](https://www.youtube.com/watch?v=cyagQl7pQJ4) - About: Scout, the guide character in the Radar videos, walks through one real finding from the public Radar sample report: AI engines describing a different, same-named company. It covers the evidence, who owns each step of the fix, and how to recheck. - Note: Scout scenes are illustrative. The evidence is the de-identified July 2026 baseline from the public sample report; the Gemini example still needs client confirmation, and no follow-up result is published. Transcript: AI found your client's name. Great. But is it talking about the right business? I'm Scout. Let's untangle one real Radar finding. This public sample report is a de-identified travel agency's July 2026 baseline. It flagged five identity confusion issues. Three marked high severity. Perplexity mixed in similarly named agencies. Gemini described a company profile that still needs the client's confirmation. Those details matter more than a headline score. Start by confirming the business facts with your client. The official name, location, history, and services. Your content owner makes those details clear on the website. Your web team adds matching organization markup. Then align relevant business listings, that's a practical assignment, with people responsible for it. After the update, check the page and its markup. Repeat comparable AI questions. Record the date, providers, prompts, and responses. Does the confusion remain? No follow-up result is published here. A changed answer doesn't prove your edit caused it. Now, the client gets a clear plan, the evidence, the owner, and the next check. One issue becomes a decision your team can explain and act on. That's Radar, the decision layer for AI visibility. I'm Scout, your guide to Radar. ### Does AI Get You? Meet Scout, Your Guide to Radar - Watch: https://www.youtube.com/watch?v=MXEqaWqyE6c - Page with transcript: https://www.pixelmojo.io/videos/meet-scout-your-guide-to-radar - Length: 0:20 - Related page: https://www.pixelmojo.io/platform - Short version (0:20): [Does AI Get Your Business? Meet Scout, Your Guide to Radar #Shorts](https://www.youtube.com/watch?v=XBx852xIrmM) - About: Scout asks whether AI gets your business, spots a gap in how AI describes a business, and notes what to check next. - Note: The AI-view and next-check graphics are illustrative examples, not a product screenshot or a measured audit result. Transcript: Oh, hey. I'm Scout, your guide to Radar. Let's see how AI understands your business and what to check next. ### When Buyers Ask AI Who to Choose, Do You Make the Shortlist? - Watch: https://www.youtube.com/watch?v=cvb10u2s4w0 - Page with transcript: https://www.pixelmojo.io/videos/do-you-make-the-ai-shortlist - Length: 0:18 - Related page: https://www.pixelmojo.io/blogs/ai-visibility-evidence-standard - About: When buyers ask ChatGPT, Claude, Perplexity and Gemini to compare options on budget, fit and proof, does your business make the shortlist? Transcript: When buyers ask AI who to choose, does your business make the shortlist? Huh? Let's take a closer look. ### What Should We Fix First? AI Search Visibility for Agencies - Watch: https://www.youtube.com/watch?v=OVGRKA4WFEY - Page with transcript: https://www.pixelmojo.io/videos/what-should-we-fix-first - Length: 0:20 - Related page: https://www.pixelmojo.io/platform - Short version (0:20): [What Should We Fix First? Radar for Agencies #Shorts](https://www.youtube.com/watch?v=_VH6s23xNaM) - About: Scout shows how an agency can answer a client's question, what should we fix first: inspect how AI describes the business, review the evidence, choose one practical change, then check again. - Note: The AI answer, service page and recheck are an illustrative example, not a real client result. Transcript: Your client asks, what should we fix first? I'm Scout. Radar helps you inspect how AI describes their business. Review the evidence. Choose one practical change. Then check again, so your client gets a clear next step. ### Website Access vs AI Answers: What Should You Check? - Watch: https://www.youtube.com/watch?v=sffxq2uJ1Gg - Page with transcript: https://www.pixelmojo.io/videos/website-access-vs-ai-answers - Length: 0:30 - Related page: https://www.pixelmojo.io/platform/sample-report - Short version (0:30): [The Site Loads. What Does AI Say? #Shorts](https://www.youtube.com/watch?v=5iYj83HzT3Y) - About: A website loading and an AI answer describing the business are two different things to inspect. Scout explains how to match the next check to the client's question: inspect page access when that is the concern, and read the sampled answer and its prompt to understand the description. - Note: This video uses illustrative diagrams, not a real client result. Transcript: The site loads. But what does AI say? A crawl check helps inspect access. A sampled answer shows what a model returned to a question. Those are different observations. Start with the client's question. Check access when that's the concern. Inspect the answer to understand the description. I'm Scout, your guide to Radar. ### What Is a Content Graph? Lloyd & Scout Explain - Watch: https://www.youtube.com/watch?v=LMHCsqzSWsc - Page with transcript: https://www.pixelmojo.io/videos/what-is-a-content-graph - Length: 3:50 - Related page: https://www.pixelmojo.io/blogs/knowledge-graph-llm-visibility-real-data - About: Lloyd and Scout walk through content graphs: how vector search finds content with a similar meaning, how a graph makes relationships explicit, why both still need good information and evidence, and how Pixelmojo uses both in structured data, Related Reading and answers grounded in relevant content and source URLs. - Note: This is an animated film. Scenes are illustrative. Transcript: Lloyd, I found three radars. This one says we should bring an umbrella. Same name. Different thing. Let's find ours. Product pages. Articles. Answers. We've got plenty of content. Now let's show how it connects. That's what a content graph does. Each dot represents something: a product, a topic, a company, or a page. Each connection says how they relate. This article is about Radar. And this Radar is a Pixelmojo product, with its own description and official page. So the line needs to say something. Exactly. About. Mentions. Made by. The relationship matters. That doesn't say Radar. It doesn't have to. Vector search can find content with a similar meaning, even when the words are different. Possible places to look. Right. A similarity score helps rank them. It doesn't prove that a claim is true. And the graph? It makes the relationships explicit. This article is about Radar. Radar is connected to AI visibility. Here's its official page. Now I can follow the connection and inspect the source. Can I add this one? Only if we can support it. Drawing a line doesn't make it true. Graphs need maintenance too. Missing connections leave gaps. Wrong connections can mislead. And vector search also needs good content and checks for weak matches. Both need care. At Pixelmojo, we use both. We define our products, services, topics, and their relationships. Some page connections are set directly, others come from content tags. Where does that show up? In the structured data on our pages, the descriptions machines can read. In Related Reading, which combines similarity with shared entities, and in our question-answering system. How does that last one work? It uses embeddings to find relevant content, including our defined entities. Their descriptions and source URLs help ground the answer. Find something relevant. Then check what it actually says. A buyer wants to know what you do, who you are, and where the evidence is. Your content should make those answers easier. Easy to find and connect. That's the job of the content graph. Yes. And Radar helps us inspect how AI describes a business and where it gets things wrong. We improve the information, then check again. We still check the answer? Always. Clearer information helps. External AI systems still choose their own sources and responses. And this radar? Still the weather. Source: Karpukhin et al., "Dense Passage Retrieval for Open-Domain Question Answering" (2020), https://arxiv.org/abs/2004.04906 ### Which Lead Should We Call First? AI Lead Qualification with Vector - Watch: https://www.youtube.com/watch?v=PX5GPSFfkpw - Page with transcript: https://www.pixelmojo.io/videos/ai-lead-qualification-with-vector - Length: 3:56 - Related page: https://www.pixelmojo.io/vector - About: Lloyd and Scout walk through how Vector qualifies an inquiry: start from the conversation, keep the evidence and the unknowns visible, apply criteria your business sets, keep the reason beside the decision, and give the seller a useful handoff. - Note: This is an animated film. The buyer scenario is illustrative. Vector is Pixelmojo's lead qualification product, not the vector search covered in our content graph video. Transcript: This one says urgent. Front of the queue? Maybe. What do they need? It didn't put that on the tag. Inquiries arrive in different ways. A loud request can hide missing details. A quiet one may contain a clear need. So let's open this one. Let's look at the conversation. That's where Vector starts. What problem are they trying to solve? Is there an active project? What is the timing, and who is involved in the decision? This message gives us the problem and the date. Useful evidence. Keep it with the inquiry. And the budget? They haven't told us. That's a question to follow up, not a number to invent. I'll leave it open. Qualification means understanding what we know, what we don't, and what deserves attention next. Start with the customers you can actually help: their problems, requirements, and the situations where your offer fits. So another business might make a different call? Yes. The criteria need to reflect your sales process. Vector is configured around your ideal customer profile, qualification signals, and routing rules. Its assessment should give the receiving team useful context. Can I see why it went that way? The reason belongs beside the decision, with the evidence behind it. Does every inquiry go straight to sales? The next step depends on what we learn. A sales conversation, useful follow-up over time, or a closer look from someone on the team. Each gets a next step. This one doesn't fit the usual pattern. Bring it to a person. Your team can inspect the rationale and change the route. With the original conversation? Yes. Give them enough context to make a considered decision. For the receiving seller, the useful part is the handoff: the need, relevant details, open questions, and why this conversation was routed to them. The inquiry arrives with its story. And the seller can start from there. The build connects qualification to the tools your team uses. We agree the CRM fields, receiving owner, and follow-up workflow. So the next person knows what to do. That's the point. The receiving team helps define the handoff. Vector is a custom build. We establish your baseline, configure the rules, connect the workflow, and test it with your team. And keep checking after launch? Yes. Compare the decisions with real outcomes and adjust where the evidence calls for it. You own the application; Pixelmojo maintains the intelligence platform. What about our urgent one? Check the need. Then choose the next step. The tag can stay. Now it has company. ### Why Am I Explaining This Again? AI Agent Handoffs with Hive - Watch: https://www.youtube.com/watch?v=YS0NBrP-eJw - Page with transcript: https://www.pixelmojo.io/videos/ai-agent-handoffs-with-hive - Length: 4:31 - Related page: https://www.pixelmojo.io/hive - About: Lloyd and Scout follow one customer request through Hive: specialized agents around shared customer context, handoffs that carry ownership, a person for uncertain cases, visible work, and a staged rollout. - Note: This is an animated film. The customer scenario is illustrative. Transcript: I already explained this downstairs. Your request arrived. The explanation didn't. Then we should find out where it went. Same question. Third door. When tools work in separate sessions, the next step can lose the history. Hive starts with that handoff. I'm carrying the case. Why am I carrying the whole conversation too? Let's follow one customer request: they want to change their service before renewal, and there's an unresolved support issue. So the next step needs more than the latest message. Exactly. The history affects what should happen next. Hive is designed to coordinate specialized agents around shared customer context: what's being requested, what happened already, and who owns the next step. The next person can pick up the thread. With access to the information their role needs. One specialist identifies the request. Another checks the relevant account or support history. A coordinator decides which configured workflow should handle the next step. And they pass the history along? The handoff should carry the context and the reason for it. Who has it now? The next owner should be clear. A handoff needs the request, relevant history, the action taken, and anything still unresolved. Otherwise it's just a different inbox. Right. Coordination needs explicit responsibilities. That support issue hasn't been resolved. Can the change go ahead? That part still needs a decision. When the case is uncertain or outside the agreed rules, bring in a person. With the whole relevant thread. So they can review it. I can see the original request, the checks already made, and the question that needs my attention. You don't have to make me tell the whole story again. That's the goal. A useful escalation arrives with context and a clear reason. The team also needs to see what the system did: the handoffs, the rationale, the owner, and the outcome. We can follow the work, too. And stop or change a workflow when the checks show something needs attention. Start with a defined workflow and a small team of agents. Test it, release to a limited group, and compare it with your baseline before expanding. So we learn where the handoffs work. And where people still need to step in. Hive's proposed twelve-week build covers discovery, a small agent team and integrations, staged deployment, then review and handover. What does the customer keep? The custom application, workflows, integrations, and their data environment. Pixelmojo operates the underlying intelligence platform. We define that boundary, along with access and operating controls, before the build. Do I need to explain it again? The next owner has the request, the relevant history, and the open question. Good. This time, the story came with me. That's the handoff we're building for. ### Lost in AI Answers? Scout Finds What to Check Next - Watch: https://www.youtube.com/watch?v=xMWNQTo9d5E - Page with transcript: https://www.pixelmojo.io/videos/lost-in-ai-answers - Length: 0:55 - Related page: https://www.pixelmojo.io/platform - Short version (0:55): [Lost in AI Answers? Scout's Next Move #Shorts](https://www.youtube.com/watch?v=sbDwnInvfkI) - About: When AI answers about a business point in different directions, Scout follows the clue, checks the evidence and picks one practical next check. A 55-second animated teaser for Radar, with sound effects only. - Note: This is an animated film with sound effects only. The services page and next-check cards are illustrative concepts, not a real client result or report. Transcript: [Waves. A map rustles.] Lost in AI answers? [Wooden signs clack. Footsteps.] [A parachute opens. Wind. Birds flutter and chirp.] [Goggles snap. A quick landing. Splash.] [Bubbles. A pufferfish puffs.] Check the evidence. (Illustrative concept.) [Paper flicks. A click.] Next check: clarify your services. (Illustrative concept.) [A folder slides over. A chime.] Know what to check next. [A bird chirps. An elastic pop.] The decision layer for AI visibility. Radar by Pixelmojo. ### Does AI Understand Your Business? Scout's Saudi Adventure (Arabic) - Watch: https://www.youtube.com/watch?v=uSUwpvcwvxc - Page with transcript: https://www.pixelmojo.io/videos/does-ai-understand-your-business-arabic - Length: 1:50 - Related page: https://www.pixelmojo.io/ar/radar - About: An AI answer calls a Jeddah dive business "professionals only", yet it welcomes beginners. Scout follows the case from the Riyadh Metro to the Red Sea: ask the way a customer asks, compare the answer with its sources and the business's own pages, then pick one priority to review and check again. Spoken in Saudi Arabic with English subtitles. - Note: This is an animated film, spoken in Saudi Arabic; the transcript is its English subtitles. The dive business and the comparisons are an illustrative example, not a real client result. Editing a page does not guarantee that an AI will recommend a business. Transcript (English subtitles): Wait… professionals only? OK, and what about your beginners? Let's see where this description came from. Before we look for the answer, we set up the question. What does your customer actually ask? Where can I find beginner diving trips in Jeddah? Language and market change how the question is asked… Well, hello! Looks like you know the way better than I do. Here it's clear you welcome beginners. But only in English. And in Arabic? The information isn't clear. Now we compare: what did the AI say? Which sources did it rely on? And what does your page say? That's a gap worth reviewing. We start by clarifying the beginner programs on the Arabic page. Then we run the same check again and see what changed. Now you have evidence to review with your team, a clear priority, and a step to start with. Radar. We review how AI understands your business, and help you decide the next step. ### How to Use Radar: Check How AI Describes Your Business (1-Minute Guide) - Watch: https://www.youtube.com/watch?v=AGH_cgK5eWw - Page with transcript: https://www.pixelmojo.io/videos/how-to-use-radar - Length: 1:00 - Related page: https://www.pixelmojo.io/platform - About: Scout walks through Radar in one minute: start a free check with your domain, email and a six-digit code, see what the six technical checks cover and what the paid 13-tool audit adds, follow the evidence behind a finding in the public sample report, then plan a fix with your team and check again. - Note: This is an animated film. The form, report and evidence on screen come from the public Radar pages; the sample report is a de-identified July 2026 audit. The code-entry, prompt and recheck steps are enlarged demonstrations. No score increase or recheck result is shown. Transcript: Does AI describe your business accurately? Let's take a closer look with Radar. Enter your domain and email, confirm the six-digit code, then run your free check. Six technical checks give you a readiness score and a first look at your site. A paid full audit covers thirteen tools, including AI-response checks across ChatGPT, Claude, Gemini and Perplexity. Inspect the responses and citations. Here, the sample report reveals confusion with another business. Review the top priority. Generate a prompt to help draft the fix. Your team reviews and makes the change. After the change, recheck. See what still needs attention. I'm Scout, your guide to Radar. ### What Is Decision-Stage AI Visibility? Lloyd & Scout Explain Radar - Watch: https://www.youtube.com/watch?v=_2ttv0ULljk - Page with transcript: https://www.pixelmojo.io/videos/what-is-decision-stage-ai-visibility - Length: 1:09 - Related page: https://www.pixelmojo.io/blogs/decision-stage-ai-visibility - About: Lloyd and Scout explain decision-stage AI visibility: when buyers ask AI which agency to choose, does your business make the shortlist? Radar's three steps check whether AI can read your site, sample what AI answers say about you with the evidence behind each answer, and hand your team a suggested fix for each finding. Your team makes the change and checks again. - Note: This is an animated film. The buyer scenario is illustrative: no real agency names, scores or results are shown. Transcript: Lloyd, when buyers ask AI which agency to choose, are we on the shortlist? That's the decision stage. And it starts with what AI can read, and say, about you. So how do we get ready for it? Radar is built for decision-stage AI visibility. Three steps. First, it checks whether AI can read your site. Pages, structured data, crawler access. Got it. Second, it samples what AI answers say about you, across ChatGPT, Claude, Gemini and Perplexity. And shows the evidence behind each answer. Third, it hands your team a suggested fix for each finding. Then we make the change, and check again? Always. AI still chooses its own answers. Radar shows you what to check, and what to fix first. One useful fix, then check again? Small steps, Scout. Finally. Something I'm built for. ### AI Didn't Mention Us. What Do We Fix? Lloyd & Scout, Before You Press Panic - Watch: https://www.youtube.com/watch?v=RaJ8nijJde4 - Page with transcript: https://www.pixelmojo.io/videos/before-you-press-panic - Length: 1:30 - Related page: https://www.pixelmojo.io/blogs/ai-visibility-evidence-standard - About: AI didn't mention your business. Lloyd and Scout look at one dated Radar finding: in a share-of-voice check on 25 September 2026, Pixelmojo wasn't detected in 20 usable answers from four AI providers, for questions about AI visibility audit platforms. Before changing anything, check the questions, read the answers, see which businesses and evidence appeared, and compare the questions with what customers actually ask. Then make a useful change, check again and record what changed. - Note: This is an animated film. The answer cards on screen are a visual reconstruction, not quotations from the actual answers. The finding is one dated sample (25 September 2026): it does not diagnose the cause or represent every buyer. Transcript: Lloyd, AI didn't mention us. What do we fix? First, let's check what that zero means. In Radar's share-of-voice check, Pixelmojo wasn't detected in twenty usable answers from four providers. About what? AI visibility audit platforms. So we're invisible? We were missing from this sample. It doesn't tell us why, or what every buyer sees. Then where do we start? Check the questions. Read the answers. See which businesses appeared, and what evidence is available. And check whether those questions match what our customers actually ask. Exactly. That helps us choose what to investigate before changing the site. Find the gap. Make a useful change. Then check again? Yes. And record what changed. You can put that away. Good. I hadn't plugged it in yet. Source: The Evidence Standard Every AI Visibility Report Should Meet (Pixelmojo, Radar records read 25 September 2026), https://www.pixelmojo.io/blogs/ai-visibility-evidence-standard ### AI Says It's the “Best.” Ask This Before You Trust It | Lloyd & Scout - Watch: https://www.youtube.com/watch?v=4ONmnXMC9uw - Page with transcript: https://www.pixelmojo.io/videos/ai-says-best - Length: 1:00 - Related page: https://www.pixelmojo.io/blogs/decision-stage-ai-visibility - About: AI says an agency is the “best.” Best for which customer? Lloyd and Scout turn a vague “best” into a question you can check. Start with a real customer and what they need: a website launch, a small team, and a site that has to work with their CRM. Put those needs in the question, then inspect the answer: does the recommendation fit, what supports that, and what's still unknown? Keeping the question and the evidence together gives you a useful starting point, not a final verdict. - Note: This is an animated film. The agency, the trophy and the answer on screen are illustrative: no real ranking, AI answer or client result is shown. Transcript: Found it! The best agency. Best for whom? It didn't say. Then start with a real customer. What do they need? A website launch. A small team. And it has to work with their CRM. Put those needs in the question. Then inspect the answer. Does the agency fit? What supports that? What's still unknown? Keep the question and the evidence together. That's a useful starting point. At least we know what this is good for. --- ## Blog (95 articles, grouped by series) ### Series: The AI Visibility Stack - [What a Wrong-Company Audit Taught Us About AI Visibility](https://www.pixelmojo.io/blogs/what-a-wrong-company-audit-taught-us-about-ai-visibility) An AI visibility audit can look credible while measuring the wrong company. What one failure taught us about entity resolution and audit integrity. Published: 2026-07-31T00:00:00.000Z | Tags: geo, generative-engine-optimization, ai-search, ai-citations, llms-txt - [From Free Check to AI Visibility Strategy: Which Next Step Fits Your Team?](https://www.pixelmojo.io/blogs/from-free-audit-to-ai-visibility-strategy) After a free AI visibility check: when one $5 audit is enough, when a pack or Pro fits, and when to hand the work to a strategy sprint. Prices as of October 2026. Published: 2026-04-22T00:00:00.000Z | Tags: ai-visibility, ai-visibility-tools, ai-visibility-audit, ai-visibility-strategy, ai-visibility-platform - [One Audit, 13 Tools: What Radar Finds That Separate Checks Miss](https://www.pixelmojo.io/blogs/why-radar-beats-running-12-tools-separately) How a Radar audit runs 13 AI visibility tools in staged batches, reads their results together, and orders the fixes. What one audit catches that separate checks miss. Published: 2026-04-15T00:00:00.000Z | Tags: ai-visibility, ai-visibility-tools, ai-visibility-audit, ai-visibility-score, ai-visibility-platform - [Your SEO Is Fine. Your AI Visibility Needs Its Own Measurement.](https://www.pixelmojo.io/blogs/your-seo-is-fine-your-ai-visibility-isnt) Rankings and backlinks do not show what ChatGPT, Claude, Gemini or Perplexity say about you. What SEO tools measure, what AI answers need, and how to check both. Published: 2026-04-09T00:00:00.000Z | Tags: ai-visibility, ai-visibility-gap, seo-vs-ai-visibility, ai-search, ai-citations - [Why We Built Radar: The Commit Trail Behind Our Own AI Visibility Fixes](https://www.pixelmojo.io/blogs/ai-visibility-stack-origin-story) How fixes on our own site became Radar, told from the git history: what we changed from October 2025 to March 2026, and what that history cannot prove. Published: 2026-04-05T00:00:00.000Z | Tags: ai-visibility, radar, case-study, llms-txt, knowledge-graph - [Radar's First Beta Weeks: What Our Records Show (Dated Note)](https://www.pixelmojo.io/blogs/50-users-free-ai-visibility-tools-what-they-were-looking-for) A dated note on Radar's private beta, 16 March to 2 April 2026: who requested access, what we recorded, and why we withdrew the "50 users" figure. Published: 2026-04-02T00:00:00.000Z | Tags: ai-visibility, ai-visibility-tools, free-tools, radar, geo ### Series: The AI Search Playbook - [We Built 2 Tools to Test If AI Engines Cite Your Pages](https://www.pixelmojo.io/blogs/aeo-page-auditor-answer-engine-citation-tester-launch) AEO Page Auditor scores pages for answer engine readiness. Answer Engine Citation Tester checks if AI engines cite your URL. Both now generate AI-ready implementation prompts via Radar. Published: 2026-03-28T00:00:00.000Z | Tags: aeo, answer-engine-optimization, aeo-page-auditor, answer-engine-tester, geo - [AI Visibility Stack: How We Monitor SEO, GEO and LLMs (2026)](https://www.pixelmojo.io/blogs/ai-visibility-stack-seo-geo-llm-monitoring-vector-hive) How we use Radar, Vector, and Hive to monitor AI visibility across SEO, GEO, and LLM channels. Real GSC data and the 3-layer monitoring framework. Published: 2026-03-22T00:00:00.000Z | Tags: ai-visibility-tools, ai-visibility-stack, ai-visibility-monitoring, seo-intelligence, ai-citation-tracking - [We Built a Platform to Run Our AI Search Playbook in One Audit](https://www.pixelmojo.io/blogs/radar-ai-visibility-platform-run-entire-playbook-60-seconds) Radar by Pixelmojo runs 13 AI visibility tools in staged batches, generates cross-tool insights, and produces AI-ready implementation prompts you paste into Claude, ChatGPT, or Cursor. Published: 2026-03-17T00:00:00.000Z | Tags: radar, ai-visibility-platform, ai-visibility-audit, ai-visibility-score, geo - [How Our AI Bot Policy Changed, November 2025 to October 2026 (Dated Note)](https://www.pixelmojo.io/blogs/why-we-blocked-ai-training-bots-and-citations-went-up) A dated note on how pixelmojo.io's robots.txt treated AI crawlers from November 2025 to October 2026, and why we withdrew the claim that blocking them raised citations. Published: 2026-03-06T00:00:00.000Z | Tags: ai-training-bots, robots-txt-strategy, ai-search, ai-citations, geo - [The AI Discoverability Stack: Four Features That Make Our Site Machine-Readable](https://www.pixelmojo.io/blogs/ai-discoverability-stack-get-cited-by-ai-search) Four features we built so AI agents and search engines can read our site directly: connected JSON-LD, an MCP endpoint, a knowledge API and one-source FAQ. Published: 2026-03-04T00:00:00.000Z | Tags: geo, generative-engine-optimization, ai-search, ai-citations, llms-txt - [GEO Playbook: Access, Content and Measurement for ChatGPT, Perplexity and Claude](https://www.pixelmojo.io/blogs/geo-playbook-get-cited-chatgpt-perplexity-claude) What you can control in generative engine optimization as of October 2026: AI crawler access, quotable pages, a clear entity, and measurement that does not fool you. Published: 2026-02-17T00:00:00.000Z | Tags: geo-playbook, generative-engine-optimization, geo, ai-citations, chatgpt-citations - [Google Traffic Dropped 33%? What the AI-Search Shift Means](https://www.pixelmojo.io/blogs/google-traffic-dropped-33-percent-ai-search-shift) Organic clicks are falling as AI answers replace search. Where your traffic actually went, what the shift means, and how to recover. Published: 2026-02-17T00:00:00.000Z | Tags: ai-search, generative-engine-optimization, geo, aeo, answer-engine-optimization - [What We Changed for AI Search by February 2026 (Dated Note)](https://www.pixelmojo.io/blogs/optimized-ai-search-pixelmojo-results) A dated note on the changes we made to our own site for AI search between October 2025 and February 2026, and the results claims we withdrew in October 2026. Published: 2026-02-17T00:00:00.000Z | Tags: geo-case-study, generative-engine-optimization, geo, ai-search-optimization, ai-search-results - [SEO vs AEO vs GEO: From Ranking in Search to Becoming the Recommended Brand](https://www.pixelmojo.io/blogs/seo-vs-geo-vs-aeo-guide-2026) Learn the difference between SEO, AEO, and GEO, and how brands can move from ranking in search to being cited in answers and recommended by AI engines. Published: 2026-02-17T00:00:00.000Z | Tags: seo-vs-geo, geo-vs-aeo, aeo-vs-geo, generative-engine-optimization, answer-engine-optimization - [How to Build a Brand That AI Search Engines Cite](https://www.pixelmojo.io/blogs/build-brand-ai-search-engines-cite) 5 branding strategies optimized for ChatGPT, Perplexity, and AI Overviews. Build a brand AI search engines actually cite and recommend. Published: 2025-06-12T00:00:00.000Z | Tags: brand-strategy, branding-tips, brand-building, brand-identity, ai-search-branding ### Series: The AX Design Playbook - [Thread-Based Agentic Experience Engineering [TBE + AXD]](https://www.pixelmojo.io/blogs/thread-based-agentic-experience-engineering-tbe-meets-axd) The unified framework connecting Thread-Based Engineering to Agentic Experience Design. How thread autonomy levels map to trust patterns and supervision models. Published: 2026-03-23T00:00:00.000Z | Tags: thread-based-engineering, ai-governance, code-quality, thread-types, z-threads - [AX Metrics: How to Measure Agentic Experience Quality Beyond Task Completion](https://www.pixelmojo.io/blogs/ax-metrics-measuring-agentic-experience-quality-beyond-task-completion) Task completion alone is a vanity metric for AI agents. The five-pillar AX metrics framework that separates agents users tolerate from agents users trust. Published: 2026-03-14T00:00:00.000Z | Tags: agentic-ux-design, agentic-experience, ax-design, ai-coworker, ax-metrics - [Agent Personality Design: Voice and Trust Framework](https://www.pixelmojo.io/blogs/agent-personality-voice-design-how-to-build-ai-coworkers-people-trust) Too much anthropomorphism can undermine trust. A practical framework for AI agent personality, tone calibration, and voice design that builds trust. Published: 2026-03-13T00:00:00.000Z | Tags: agentic-ux-design, agentic-experience, ax-design, ai-coworker, agent-personality-design - [Conversation Flow Architecture [4 Design Layers]](https://www.pixelmojo.io/blogs/conversation-flow-architecture-designing-multi-turn-agent-interactions) LLMs show a 39% average performance drop in multi-turn conversations. Learn 4 conversation flow layers: state machines, context persistence, handoff topologies, and state recovery for production agents. Published: 2026-03-11T00:00:00.000Z | Tags: agentic-ux-design, agentic-experience, ax-design, ai-coworker, conversation-flow-architecture - [Trust Design Patterns: How Users Learn to Rely on AI Coworkers](https://www.pixelmojo.io/blogs/ax-design-trust-patterns-how-users-learn-to-rely-on-ai-coworkers) Only 6% of companies fully trust AI agents for core processes. This guide covers the six trust patterns, progressive autonomy, and recovery cycles that make agentic experiences trustworthy. Published: 2026-03-08T00:00:00.000Z | Tags: agentic-ux-design, agentic-experience, ax-design, ai-coworker, trust-design-patterns - [AX Design Explained: The 2026 Guide to Agentic Experience](https://www.pixelmojo.io/blogs/what-is-ax-design-complete-guide-agentic-experience-2026) AX (agentic experience) design explained: what it is, how it differs from UX, and how to design for an era where AI agents are the users. Published: 2026-03-06T00:00:00.000Z | Tags: agentic-ux-design, agentic-experience, ax-design, ai-coworker, what-is-ax-design ### Series: Multi-Agent AI - [From UX to AX: What Design Looks Like When AI Becomes Your Co-Worker](https://www.pixelmojo.io/blogs/from-ux-to-ax-design-when-ai-becomes-coworker) UX design is splitting into a new discipline called AX (Agentic Experience). This guide covers the six patterns, four protocols, and product redesigns shaping interfaces in 2026. Published: 2026-02-17T00:00:00.000Z | Tags: agentic-ux-design, agentic-experience, ax-design, ai-coworker-ux, generative-ui - [The Dawn of Agentic AI: From Chatbots to Co-workers in 2026](https://www.pixelmojo.io/blogs/dawn-of-agentic-ai-chatbots-to-coworkers-2026) AI is no longer just answering questions; it is taking action. The shift from assistive chatbots to agentic AI co-workers is the defining technology transition of 2026. What this means for businesses and why self-verification changes everything. Published: 2026-01-10T00:00:00.000Z | Tags: agentic-ai-2026, ai-agents-vs-chatbots, autonomous-ai-agents, ai-coworkers, self-verification-ai - [Multi-Agent AI Platform: Build vs Buy - Pricing & TCO (2026)](https://www.pixelmojo.io/blogs/multi-agent-ai-platform-buyers-guide-build-vs-buy-comparison) We compared CrewAI, AutoGen, LangGraph, and 4 SaaS platforms on real 3-year costs. One option costs 47% less than enterprise SaaS. Full tables inside. Published: 2026-01-05T00:00:00.000Z | Tags: multi-agent-ai-buyer-guide, ai-agent-platform-comparison, build-vs-buy-ai-agents, enterprise-ai-evaluation, ai-agent-tco-analysis - [Multi-Agent AI Systems Explained: When One AI Is Not Enough](https://www.pixelmojo.io/blogs/multi-agent-ai-systems-explained-when-one-ai-isnt-enough) Why single AI agents fail at scale and how multi-agent orchestration solves it. Architecture patterns, shared intelligence, and why 95% of AI pilots show no measurable impact. Published: 2026-01-02T00:00:00.000Z | Tags: multi-agent-ai-systems, ai-agent-orchestration, multi-agent-orchestration, ai-agents-2026, enterprise-ai-architecture ### Series: AI Technical Debt - [Lakbay AI: What We Built and What We Withdrew (Dated Note)](https://www.pixelmojo.io/blogs/lakbay-ai-case-study-thread-based-engineering-in-production) A dated note on our February 2026 Lakbay AI case study: what the travel concierge is, what its repository history shows, and the timeline, speed and security claims we withdrew. Published: 2026-02-08T00:00:00.000Z | Tags: thread-based-engineering, z-thread, zero-touch-thread, ai-case-study, lakbay-ai - [Claude Code Technical Debt Mitigation: The Complete Production Guide](https://www.pixelmojo.io/blogs/claude-code-technical-debt-mitigation-guide) Prevent AI-generated technical debt with Claude Code using CLAUDE.md optimization, security-first prompting, and production guardrails. Research-backed strategies that deliver +5-10% improvement. Published: 2026-02-01T00:00:00.000Z | Tags: claude-code, claude-code-technical-debt, claude-md, ai-code-quality, ai-technical-debt - [Thread-Based Engineering: How We Keep AI-Assisted Code Reviewable](https://www.pixelmojo.io/blogs/thread-based-engineering-prevents-ai-technical-debt) How we govern AI-assisted development: two mandatory human checkpoints, the gates every change passes before it merges, and what the 2025 data says about AI code. As of October 2026. Published: 2026-02-01T00:00:00.000Z | Tags: thread-based-engineering, ai-governance, technical-debt-prevention, hive-ai, ai-coding-governance - [84% of Developers Use AI Tools. 45% of AI Code Has Flaws.](https://www.pixelmojo.io/blogs/vibe-coding-technical-debt-crisis-2026-2027) 84% of developers use or plan to use AI tools, yet only a third trust their accuracy, and 45% of AI-generated code samples failed security tests. The 2026 research data, the risks, and governance patterns that work. Published: 2026-01-31T00:00:00.000Z | Tags: vibe-coding, technical-debt, ai-coding, agentic-coding, ai-coworkers ### Series: Thread-Based Engineering - [Thread-Based Engineering: The Framework for Scaling AI Development](https://www.pixelmojo.io/blogs/thread-based-engineering-scaling-ai-development) The definitive guide to Thread-Based Engineering: 7 thread types, governance alignment, a production case study (Lakbay AI), and the research on AI code quality, including the Veracode finding that models failed to write XSS-safe code 86% of the time. Published: 2026-01-24T00:00:00.000Z | Tags: thread-based-engineering, ai-assisted-development, parallel-workflows, multi-agent-orchestration, ai-productivity ### Series: AI Native Agency - [How to Budget for Marketing Design: Comparing Agency Quotes in 2026](https://www.pixelmojo.io/blogs/budgeting-marketing-design-ai-automation-vs-traditional-agency-fees) How to budget for marketing design: what drives agency cost, how to compare quotes on the same terms, and how to audit what you spend now. Prices dated October 2026. Published: 2025-10-12T00:00:00.000Z | Tags: budgeting-marketing-design, ai-automation-vs-traditional-agency, ai-native-agency-cost, marketing-design-budget, agency-fees-comparison - [AI-Native vs Traditional Design Agency: How to Choose in 2026](https://www.pixelmojo.io/blogs/ai-native-design-agency-vs-traditional-agency-complete-guide) How AI-native and traditional design agencies differ in process, pricing and fit, how to test an agency's AI claims, and what to ask before you sign. As of October 2026. Published: 2025-09-28T00:00:00.000Z | Tags: ai-native-design-agency, traditional-design-agency, ai-powered-creative-agency, design-agency-comparison, ai-design-tools ### Series: Growth Marketing - [AI Growth Marketing: Where AI Helps Across the Customer Lifecycle](https://www.pixelmojo.io/blogs/the-definitive-guide-to-growth-marketing-in-the-age-of-ai-strategies-frameworks-and-real-world-dominance) Where AI actually helps in growth marketing as of October 2026, from acquisition to retention, how to start with one workflow, and where people still need to decide. Published: 2025-08-30T00:00:00.000Z | Tags: ai-marketing, growth-marketing, b2b-marketing, agency, growth-hacking - [Growth Marketing vs. Traditional Marketing: The Complete Guide](https://www.pixelmojo.io/blogs/growth-marketing-vs-traditional-marketing-the-complete-guide) Transform your marketing from cost center to revenue engine. This definitive guide reveals why growth marketing outperforms traditional campaigns, with actionable frameworks, tools, and strategies for building systematic, data-driven growth that scales predictably. Published: 2025-06-21T00:00:00.000Z | Tags: growth-marketing, traditional-marketing-vs-growth-marketing, growth-marketing-framework, aarrr-pirate-metrics, customer-lifetime-value ### Series: Southeast Asia UX - [UI/UX Design Best Practices for Southeast Asia SaaS: Localization, Accessibility, Conversion](https://www.pixelmojo.io/blogs/ui-ux-design-best-practices-for-southeast-asia-saas-localization-accessibility-conversion) An enterprise-ready guide to designing SaaS for Southeast Asian markets. Sourced data from Google-Temasek-Bain, GSMA, and Statista on localization, payment ecosystems, mobile-first design, accessibility compliance, and conversion optimization across ASEAN. Published: 2025-07-26T00:00:00.000Z | Tags: ui-ux-design-southeast-asia, saas-design-asean, localization-best-practices, accessibility-saas-design, conversion-optimization-sea - [Mastering UX Design in the Philippines: A Guide to Crafting Exceptional User Experiences](https://www.pixelmojo.io/blogs/mastering-ux-design-in-the-philippines-a-guide-to-crafting-exceptional-user-experiences) Master UX design for the Philippine market with sourced data from DataReportal, BSP, and GCash. 97.5M internet users, 88% mobile web traffic, 57.4% digital payments; practical frameworks for mobile-first design, local payment integration, and cultural considerations that drive conversion. Published: 2025-06-12T00:00:00.000Z | Tags: ux-design-philippines, filipino-user-behavior, mobile-first-design-philippines, philippine-digital-experience, user-experience-design ### Series: Design Psychology - [Why Beautiful Design Fails to Sell?](https://www.pixelmojo.io/blogs/why-beautiful-design-fails-to-sell) Discover why award-winning beautiful designs often have terrible conversion rates. This comprehensive guide reveals how to escape the 'pretty but pointless' trap and build growth-driven design that transforms visitors into customers through strategic, data-driven approaches. Published: 2025-06-21T00:00:00.000Z | Tags: beautiful-design-conversion, growth-driven-design, conversion-rate-optimization, design-fails-to-convert, aesthetic-vs-functional-design - [The Aesthetic-Usability Effect: Why Good-Looking Designs Feel Easier to Use](https://www.pixelmojo.io/blogs/the-aesthetic-usability-effect-why-good-looking-designs-feel-easier-to-use) The Aesthetic-Usability Effect means users perceive beautiful designs as more usable. This guide covers the psychology, practical playbook, and real-world examples from Apple, Airbnb, and Google. Published: 2025-06-12T00:00:00.000Z | Tags: aesthetic-usability-effect, ux-design-psychology, beautiful-design-principles, user-experience-design, design-psychology ### Standalone Articles - [The Evidence Standard Every AI Visibility Report Should Meet](https://www.pixelmojo.io/blogs/ai-visibility-evidence-standard) Our proposed AI Visibility Evidence Standard, v1: eight things every AI visibility report should disclose, tested on a real Radar audit of our own site. Published: 2026-09-25T00:00:00.000Z | Tags: ai-visibility, ai-search-visibility, ai-brand-visibility, ai-recommendations, geo - [One Page, 64,191 Impressions, Zero Clicks in 87 Days](https://www.pixelmojo.io/blogs/zero-click-impressions-search-console-investigation) A page took 64,191 Search Console impressions and zero clicks in 87 days. What the data shows, what it cannot show, and why it explained none of our lost traffic. Published: 2026-09-10T00:00:00.000Z | Tags: ai-search, geo, generative-engine-optimization, ai-citations, search-console - [The Directed Grid: How AI Should Work Inside a B2B Company](https://www.pixelmojo.io/blogs/directed-grid-ai-operating-model) AI in a B2B company should run as a directed loop: a human sets the question, Radar measures, Vector qualifies, Hive builds, and a human decides. Full model. Published: 2026-08-23T00:00:00.000Z | Tags: directed-grid, ai-operating-model, human-in-the-loop, ai-governance, agent-orchestration - [Before You Hire a GEO Agency: 4 Green Flags and 5 Red Flags](https://www.pixelmojo.io/blogs/before-you-hire-a-geo-agency) How to evaluate a GEO agency before you sign. Four green flags, five red flags, and the baseline evidence any credible AI search partner should show you first. Published: 2026-08-02T00:00:00.000Z | Tags: geo, generative-engine-optimization, ai-search, ai-citations, seo-vs-geo - [We Audit AI Visibility for a Living. So We Audited Ourselves.](https://www.pixelmojo.io/blogs/we-audited-our-own-ai-architecture) Can you trust the score an AI visibility tool gives you, tomorrow as well as today? We test our own scoring weekly and audited our whole stack. Here is the proof. Published: 2026-07-22T00:00:00.000Z | Tags: claude-code, claude-md, context-engineering, ai-coding, ai-technical-debt - [AEO Score Explained: What It Measures and How to Improve It](https://www.pixelmojo.io/blogs/aeo-score-explained-checkers-grades-improvement) What is a good AEO score? See what AEO checkers actually measure, how grades work, real data from 59 audits, and the fixes that raise a failing score. Published: 2026-07-18T00:00:00.000Z | Tags: aeo, answer-engine-optimization, aeo-score, aeo-checker, aeo-audit - [Decision-Stage AI Visibility: The Engines Buyers Ask](https://www.pixelmojo.io/blogs/decision-stage-ai-visibility) Buyers ask AI which option to choose before they reach your site. Decision-stage AI visibility is whether you win that recommendation, not just appear. Published: 2026-07-12T00:00:00.000Z | Tags: decision-stage-ai-visibility, ai-recommendation-optimization, answer-layer-vs-decision-layer, score-you-can-defend, ai-visibility-audit - [What Does Grok Say About Your Brand? We Checked. It Got Ours Wrong.](https://www.pixelmojo.io/blogs/what-does-grok-say-about-your-brand) Grok answers brand questions for 117M monthly users per the SpaceX S-1. We measured what it says, and it got our own brand wrong. Check yours today. Published: 2026-07-09T00:00:00.000Z | Tags: grok, grok-ai, xai, grok-brand-visibility, ai-visibility - [No Brand Controls Its AI Recommendations. Measure This Instead](https://www.pixelmojo.io/blogs/no-brand-controls-ai-recommendations) You cannot control what AI recommends about your brand. Here is why AI answers are volatile by design, and the five things to measure instead. Published: 2026-06-28T00:00:00.000Z | Tags: ai-visibility, decision-stage-ai-visibility, generative-engine-optimization, answer-engine-optimization, ai-search - [AI Visibility Is an Evidence Architecture Problem, Not a Content Volume Problem](https://www.pixelmojo.io/blogs/ai-visibility-evidence-architecture) Publishing more content will not make you visible in AI answers. Evidence architecture, your claims, entities, sources, and structure, is what gets you cited. Published: 2026-06-27T00:00:00.000Z | Tags: ai-visibility, evidence-architecture, generative-engine-optimization, answer-engine-optimization, ai-search - [A Score You Can Defend: How Radar Scores AI Visibility](https://www.pixelmojo.io/blogs/a-score-you-can-defend-how-radar-scores-ai-visibility) Most AI visibility scores are opaque grades you cannot defend. Here is how Radar scores AI visibility in three separated layers, with a trail behind every number. Published: 2026-06-25T00:00:00.000Z | Tags: radar, ai-visibility-platform, ai-visibility-audit, ai-visibility-score, decision-stage-ai-visibility - [Google Preferred Sources: The User-Controlled AEO Lever](https://www.pixelmojo.io/blogs/google-preferred-sources-ai-overviews) Google Preferred Sources is the one AI visibility lever your audience controls, not the model. Here is how it works, who qualifies, and how to earn it. Published: 2026-06-23T00:00:00.000Z | Tags: google-preferred-sources, preferred-sources, ai-overviews, google-ai-mode, ai-search - [From Executor to Orchestrator: Legacy UX to AX Design](https://www.pixelmojo.io/blogs/from-executor-to-orchestrator-legacy-ux-to-ax-design) The experience designer is evolving from executor to orchestrator. Why legacy UX did not get replaced by AX Design, it got extended, and how to make the climb. Published: 2026-06-21T00:00:00.000Z | Tags: agentic-experience-design, ax-design, agentic-ux-design, agentic-experience, ai-coworker - [Google Says You Don't Need llms.txt. Here's the Catch.](https://www.pixelmojo.io/blogs/google-says-you-dont-need-llms-txt) Google says llms.txt is unnecessary. Chrome Lighthouse audits it anyway. We fact-checked five studies on what llms.txt really does for AI visibility in 2026. Published: 2026-06-12T00:00:00.000Z | Tags: llms-txt, llms-txt-google, llms-txt-seo, llms-txt-ai-citations, geo - [Brand Disambiguation: When AI Confuses Your Brand With Someone Else](https://www.pixelmojo.io/blogs/brand-disambiguation-ai-entity-confusion) When AI engines link your brand to the wrong same-named entity, you still get cited, but the citation points at someone else. Here is how brand disambiguation fails and how to fix it. Published: 2026-06-05T00:00:00.000Z | Tags: brand-disambiguation, entity-linking, named-entity-disambiguation, ai-brand-identity, same-name-confusion - [Reddit Brand Monitor: What AI Learns About You on Reddit](https://www.pixelmojo.io/blogs/reddit-brand-monitor-ai-visibility-tool) Reddit is the most-cited source in AI answers. The Reddit Brand Monitor finds what is said about your brand there, scores it, and flags AI-generated seeded posts. Published: 2026-06-04T00:00:00.000Z | Tags: reddit-brand-monitor, llm-seeding, reddit-mentions, brand-monitoring, reddit-ai-visibility - [YouTube Brand Monitor: What AI Hears About Your Brand](https://www.pixelmojo.io/blogs/youtube-brand-monitor-ai-visibility-tool) The YouTube Brand Monitor tracks what is said about your brand on YouTube, scores it on five dimensions, and reads the actual transcripts so you see the coverage AI models may draw on. Published: 2026-06-04T00:00:00.000Z | Tags: youtube-brand-monitor, youtube-mentions, video-brand-tracking, creator-coverage, brand-monitoring - [How Radar Fix Prompts and the AI Advisor Fix Your AEO](https://www.pixelmojo.io/blogs/radar-fix-prompts-ai-advisor-fix-aeo-score) A failing AEO score is only useful if you can fix it. Here is how Radar fix prompts and the AI advisor turn audit findings into shipped fixes, no rewrite required. Published: 2026-06-03T00:00:00.000Z | Tags: radar, ai-fix-prompts, fix-prompts, ai-prompt-generator, implementation-threads - [Why 9 in 10 Websites Fail AEO (And How to Fix It)](https://www.pixelmojo.io/blogs/why-most-websites-fail-aeo-answer-engine-optimization) We analyzed 59 real AEO audits from the Radar platform. The average score is 26 out of 100 and 9 in 10 sites scored below 40. Here is why, and how to fix yours. Published: 2026-06-03T00:00:00.000Z | Tags: aeo, answer-engine-optimization, aeo-page-auditor, geo, generative-engine-optimization - [AI Monitoring vs AI Technical Readiness: Why You Need Both (2026)](https://www.pixelmojo.io/blogs/ai-monitoring-vs-ai-technical-readiness) AI monitoring tracks what AI says about your brand. AI technical readiness checks whether AI can reach and read your site. Some tools now do both. Here is how the stack fits together. Published: 2026-05-29T00:00:00.000Z | Tags: ai-monitoring, ai-visibility, ai-visibility-tools, ai-technical-readiness, ai-visibility-platform - [AI Agency Code Ownership: Hire Without Lock-In](https://www.pixelmojo.io/blogs/ai-agency-code-ownership-without-vendor-lock-in) AI agencies that retain your IP can cost several times more over 3 years. Contract clauses, red flags, and the Build + Platform + Performance model that ends vendor lock-in. 2026 guide. Published: 2026-05-27T00:00:00.000Z | Tags: ai-code-ownership, ai-agency-code-ownership, ai-vendor-lock-in, own-code-ai-development, ai-agency-contract - [Google Information Agents and Content Freshness (Dated Note)](https://www.pixelmojo.io/blogs/google-information-agents-content-freshness-ai-search) A dated note on what Google announced about information agents at I/O 2026, what we inferred about freshness, and why we no longer present that inference as fact. Published: 2026-05-25T00:00:00.000Z | Tags: google-information-agents, ai-search, geo, seo-vs-geo, ai-citations - [Anthropic Agent SDK Hooks: TypeScript Reference](https://www.pixelmojo.io/blogs/anthropic-agent-sdk-hooks-typescript-reference) Programmatic Anthropic Agent SDK hooks reference. The core events, full TypeScript signatures, PreToolUse, PostToolUse, Stop, SubagentStop, UserPromptSubmit with worked examples. Published: 2026-05-23T00:00:00.000Z | Tags: anthropic-agent-sdk, claude-agent-sdk, typescript-hooks, claude-code-hooks, pretooluse - [Gemini, YouTube and AI Visibility: A Dated Note on What Changed and When](https://www.pixelmojo.io/blogs/gemini-25-youtube-ai-readable) A dated note on Gemini 2.5 and YouTube video understanding: the real 2025 dates, what our YouTube Brand Monitor measures, and the claims we withdrew in October 2026. Published: 2026-05-15T00:00:00.000Z | Tags: youtube-ai-visibility, youtube-brand-monitor, video-citations, creator-coverage, youtube-citations - [Radar Assessed 50 Known Brands for AI Readiness. Scores Ran From 4 to 88.](https://www.pixelmojo.io/blogs/50-brands-audited-half-invisible-to-ai-search) First findings from the Radar Brand Index. 50 named brands assessed with Radar's AI Readiness Score. Stripe and BetterUp lead at 88/100. Hims and Hers hit 4/100. Radar could not scan three of them at all. Here is what the data says. Published: 2026-05-09T00:00:00.000Z | Tags: ai-visibility, ai-visibility-audit, ai-visibility-score, ai-visibility-platform, brand-index - [Your AI Visibility Score Is Meaningless Without Live LLM Queries](https://www.pixelmojo.io/blogs/ai-visibility-score-needs-live-llm-queries) Static AI SEO checks never query an LLM. They infer visibility from proxies. Static analysis cannot tell you what ChatGPT says about your brand. Only asking ChatGPT can. Published: 2026-05-05T00:00:00.000Z | Tags: ai-visibility, ai-visibility-score, ai-visibility-platform, ai-visibility-tools, ai-visibility-audit - [Radar is GA: A 6-Tool Free Tier, $199 Retainer, and What We Shipped](https://www.pixelmojo.io/blogs/radar-ga-freemium-launch) Radar by Pixelmojo is generally available. Free tier runs 6 technical readiness tools. Paid from $5 per audit unlocks 7 more LLM-powered tools. Here is the launch story and the pricing logic. Published: 2026-04-19T00:00:00.000Z | Tags: radar, ai-visibility-platform, ai-visibility-audit, ai-visibility-score, ai-technical-readiness - [We Analyzed 82 Real AI Visibility Audits. Here Is What the Data Shows.](https://www.pixelmojo.io/blogs/state-of-ai-visibility-2026-benchmarks-60-domain-audits) Original benchmark data from 82 real Radar platform audits across 6 core industries. Average AI readiness score: 45/100. Only 1 domain has scored an A so far. Here are the findings. Published: 2026-04-12T00:00:00.000Z | Tags: ai-visibility, ai-visibility-tools, ai-visibility-audit, ai-visibility-score, ai-visibility-platform - [How to Track AI Citations: A Practical Guide to ChatGPT, Perplexity, Claude & Gemini](https://www.pixelmojo.io/blogs/how-to-track-ai-citations-chatgpt-perplexity-claude-gemini) Track what ChatGPT, Perplexity, Claude, and Gemini say about your brand. Free and paid methods, tools compared, and step-by-step setup. Published: 2026-04-11T00:00:00.000Z | Tags: ai-citations, ai-search, citation-tracking, ai-visibility, ai-visibility-tools - [Best AI Visibility Tools (2026): 10 Options Compared](https://www.pixelmojo.io/blogs/best-ai-visibility-tools-2026) Compare 10 AI visibility tools with pricing checked in September 2026: engines tracked, AI crawler and llms.txt checks, free options, and how to choose. Published: 2026-04-10T00:00:00.000Z | Tags: ai-visibility, ai-visibility-tools, ai-visibility-audit, ai-visibility-audit-tools, ai-search-visibility - [What Is AI Technical Readiness? (And Why Monitoring Alone Is Not Enough)](https://www.pixelmojo.io/blogs/what-is-ai-technical-readiness) AI Technical Readiness is the infrastructure layer that ensures AI can crawl, parse, and cite your site. Monitoring shows symptoms. Technical readiness checks the infrastructure behind them. Published: 2026-04-08T00:00:00.000Z | Tags: ai-technical-readiness, ai-visibility, ai-visibility-audit, ai-visibility-tools, ai-visibility-platform - [Ghost Protocol: Multi-Agent Engineering Framework for GitHub Copilot](https://www.pixelmojo.io/blogs/ghost-protocol-thread-based-multi-agent-engineering-ai-coding) Ghost Protocol gives GitHub Copilot a team of 8 named specialist agents running 9 disciplined execution patterns. One installer script. Agents execute, leave clean results, disappear. Published: 2026-04-01T00:00:00.000Z | Tags: ghost-protocol, github-copilot, multi-agent, ai-coding, copilot-framework - [Radar v2: From Technical Audit to AI Intelligence Platform](https://www.pixelmojo.io/blogs/radar-v2-technical-audit-to-intelligence-platform) Radar now runs 13 AI visibility tools in staged batches with DIY implementation features: AI prompt generator, 5 implementation threads, llms.txt and schema generators, single-tool re-verify, and progress tracking. Audit, understand, fix. Published: 2026-03-30T00:00:00.000Z | Tags: radar, ai-visibility-platform, ai-visibility-audit, ai-visibility-score, geo - [How to Use Radar: Free Check, Full Audit, and AI Visibility Fixes](https://www.pixelmojo.io/blogs/radar-user-guide-ai-visibility-platform) How to use Radar as of October 2026: run the free technical check, unlock the full 13-tool audit, read the evidence in AI answers, and turn findings into fixes. Published: 2026-03-28T00:00:00.000Z | Tags: radar, ai-visibility-platform, ai-visibility-audit, ai-visibility-score, geo - [How We Retrofitted 21 Posts With StatBlocks and Speakable Schema (Dated Note)](https://www.pixelmojo.io/blogs/how-we-optimized-21-posts-for-ai-citation-aeo-implementation) A dated note on our 27 March 2026 blog retrofit: what we changed in 21 posts, what we expected it to do for AI citations, and what the evidence since says. Published: 2026-03-27T00:00:00.000Z | Tags: geo, generative-engine-optimization, aeo, answer-engine-optimization, ai-search - [How We Built a Multi-Channel AI Sales Agent in One TBE Session](https://www.pixelmojo.io/blogs/how-we-built-multi-channel-ai-sales-agent-one-tbe-session) Case study: extending Vector from chat-only to email replies, broadcasts, and delivery tracking in a single Thread-Based Engineering session. Real code, real architecture. Published: 2026-03-25T00:00:00.000Z | Tags: thread-based-engineering, ai-governance, code-quality, thread-types, z-threads - [10 Free AI Visibility Tools to Test Your Site (2026)](https://www.pixelmojo.io/blogs/free-ai-visibility-tools-complete-guide) Check how ChatGPT, Perplexity, and Claude see your website. 10 AI visibility tools (most free, AEO page auditor and citation tracker from $5): bot access checker, robots.txt analyzer, citation tracker, Reddit monitor, YouTube monitor, llms.txt validator, llms.txt generator, AI readiness scorer, AEO page auditor, and answer engine citation tester. Published: 2026-02-27T00:00:00.000Z | Tags: ai-visibility, geo-tools, ai-seo-tools, free-tools, geo - [AI Product Development in the Philippines: Why Global CTOs Are Building Here](https://www.pixelmojo.io/blogs/ai-product-development-philippines-cto-guide) The Philippines AI development market is not about cheaper rates. It is about owned products, senior methodology-driven teams, and a timezone you can plan around. A practical evaluation framework for CTOs. Published: 2026-02-25T00:00:00.000Z | Tags: ai-product-development, llm-integration, rag-systems, multi-agent, agentic-ai - [The Junior Developer Extinction Problem: Why AI Technical Debt Needs Human Apprentices](https://www.pixelmojo.io/blogs/junior-developer-extinction-ai-technical-debt-human-apprentices) 54% of engineering leaders plan to hire fewer juniors. The math looks right until you factor in who fixes AI-generated technical debt. A framework for CTOs rethinking their talent pipeline. Published: 2026-02-25T00:00:00.000Z | Tags: junior-developers, junior-developer-hiring, talent-pipeline, engineering-leadership, ai-technical-debt - [How We Built a Knowledge Graph That LLMs Actually Cite (With Real Data)](https://www.pixelmojo.io/blogs/knowledge-graph-llm-visibility-real-data) We built a cross-site knowledge graph connecting two domains via JSON-LD entity linking. Here is the architecture, the code patterns, and the real analytics from the first week. Published: 2026-02-25T00:00:00.000Z | Tags: knowledge-graph, knowledge-graph-seo, knowledge-graph-implementation, entity-linking, entity-resolution - [What Is an AI-Native Agency? Definition & Examples](https://www.pixelmojo.io/blogs/what-is-an-ai-native-agency-definition-guide) An AI-native agency builds with AI at the core, not bolted on. The definition, real examples, and how it differs from a traditional shop. Published: 2026-02-25T00:00:00.000Z | Tags: ai-native-agency, ai-native-agencies, agency, b2b-marketing, growth-marketing - [Your llms.txt Is Already Stale. Here's How to Fix It.](https://www.pixelmojo.io/blogs/llms-txt-static-vs-dynamic-implementation-guide) Static llms.txt files go stale the moment you publish new content. This guide covers what llms.txt actually does, why 844K sites got it wrong, and how to build a dynamic version in Next.js. Published: 2026-02-17T00:00:00.000Z | Tags: llms-txt, llms-txt-implementation, llms-txt-guide, llms-txt-next-js, dynamic-llms-txt - [AI Lead Qualification Workflows: DIY Scoring, Human Review, and Vector](https://www.pixelmojo.io/blogs/ai-lead-qualification-replace-hubspot-ai-agent) How our contact form scores, answers and routes leads as of October 2026, where human review belongs, and when a team needs Vector instead. Published: 2026-02-15T00:00:00.000Z | Tags: vector, lead-qualification, ai-sales-agent, b2b-lead-scoring, ai-lead-scoring - [Claude Code Hooks: Corrections to Our February 2026 Guide (Dated Note)](https://www.pixelmojo.io/blogs/claude-code-hooks-production-quality-ci-cd-patterns) A dated note on our February 2026 Claude Code hooks guide: why its config examples would not have worked, the correct shape from the official reference, and what we run instead. Published: 2026-02-14T00:00:00.000Z | Tags: claude-code-hooks, claude-code, claude-code-ci-cd, hooks-lifecycle-events, production-quality - [Context Engineering Beyond CLAUDE.md: The 5-Layer Hierarchy](https://www.pixelmojo.io/blogs/context-engineering-ai-coding-agents-beyond-claude-md) CLAUDE.md is just layer one. The five-layer context hierarchy, memory patterns, and subagent strategies that separate productive AI coding from prompt guessing. With working examples. Published: 2026-02-14T00:00:00.000Z | Tags: context-engineering, claude-md, claude-code, ai-coding-agents, prompt-engineering - [Slopsquatting and AI Supply Chain Attacks: A Defense Guide](https://www.pixelmojo.io/blogs/slopsquatting-ai-supply-chain-attacks-defense-guide) AI tools hallucinate 19.7% of package names. Attackers register them as malware. Learn how slopsquatting works and layered defense strategies. Published: 2026-02-14T00:00:00.000Z | Tags: slopsquatting, supply-chain-attacks, ai-security, package-hallucination, ai-coding-security - [7 AI Prompts That Kill Bad Product Ideas Before You Waste $100K](https://www.pixelmojo.io/blogs/ai-prompts-validate-product-ideas-fast) Stop spending months on discovery. These 7 AI prompts help product teams validate ideas in 48 hours, identify fatal flaws early, and build products people actually want to pay for. Copy-paste ready frameworks included. Published: 2025-12-12T00:00:00.000Z | Tags: ai-product-validation, product-development, startup-validation, ai-prompts, product-market-fit - [How Production AI Agents Solve Real Business Problems: Lessons From Our Own Sales Agent](https://www.pixelmojo.io/blogs/how-production-ai-agents-solve-business-pain-points) What separates a production AI agent from a demo, shown through Vector, the sales agent on our own site: channels, qualification, guardrails, hand-off, and what retrieval can and cannot fix. As of October 2026. Published: 2025-11-08T00:00:00.000Z | Tags: production-ai-systems, rag-architecture, vector-databases, multi-agent-orchestration, ai-agent-platform - [The UX Evolution: How Strategic Experience Architects Are Redefining Design in the AI Era](https://www.pixelmojo.io/blogs/ux-designer-to-strategic-experience-architect-ai-transformation) Nielsen Norman Group reports that critical thinking, creativity, and taste are becoming the key differentiators as AI tools handle routine UX tasks. Learn how top UX professionals are evolving into Strategic Experience Architects who orchestrate AI while focusing on strategic thinking and business outcomes. Published: 2025-11-01T00:00:00.000Z | Tags: ux-designer-career-evolution, strategic-experience-architect, ai-powered-ux-design, ux-automation-tools, future-of-ux-design - [Why AI-First Customer Service Is the New 'Press 1 for Sales' (and Why You're Losing Customers)](https://www.pixelmojo.io/blogs/ai-first-customer-service-automation-trap) Intent detection and risk-tier routing sound smart but ignore human psychology. Gartner reports 64% of customers prefer companies not use AI for service. Industry observations suggest AI-first approaches significantly increase abandonment compared to human-first strategies. Route by emotional value, not transaction stakes. Published: 2025-10-19T00:00:00.000Z | Tags: ai-customer-service, customer-experience-automation, ai-chatbots, conversational-ai, customer-service-strategy - [The AI Copilot Stack Guide: Corrections and What We Withdrew (Dated Note)](https://www.pixelmojo.io/blogs/complete-guide-ai-copilot-stack-multimodal-tools-developer-productivity) A dated note on our 2025 AI copilot stack guide: the install commands and tool names that were wrong, the results and ROI figures we withdrew, and what we use today. Published: 2025-09-23T00:00:00.000Z | Tags: ai-copilot-stack, multimodal-ai-tools, developer-productivity, claude-code-setup, cursor-ai-workflow - [AI Design Control Tower: The Idea and What We Withdrew (Dated Note)](https://www.pixelmojo.io/blogs/ai-design-control-tower) A dated note on our September 2025 AI Design Control Tower post: the idea of connecting product data to design decisions, and the results and offer we withdrew in 2026. Published: 2025-09-18T00:00:00.000Z | Tags: ai-design-operations, design-systems-automation, product-analytics-design, ai-driven-ux, design-ops-framework - [Why Your Design Team's Next Hire Should Think Like a Computer Scientist](https://www.pixelmojo.io/blogs/why-your-design-teams-next-hire-should-think-like-a-computer-scientist) What computational thinking means for design teams, how it shows up in components, tokens and rules, and what to look for when you hire. With examples from our own system. Published: 2025-09-15T00:00:00.000Z | Tags: design, computational-thinking, growth-os, ux, philippines - [Consumer Behavior in Marketing: Factors, Technology and Research Methods](https://www.pixelmojo.io/blogs/consumer-behavior-in-marketing-strategies-factors-technology-role-and-research-methods) What shapes buying decisions, how technology is changing where people research, and which research methods answer which questions. With our own dated data, as of October 2026. Published: 2025-06-29T00:00:00.000Z | Tags: consumer-behavior, marketing-psychology, behavioral-marketing, customer-insights, marketing-research - [Tools You Didn't Know Your Agency Needed](https://www.pixelmojo.io/blogs/tools-you-didnt-know-your-agency-needed) Discover the specialized growth marketing tools and technologies that separate high-performing agencies from the competition. This comprehensive guide reveals the modern tech stack that drives predictable ROI and client retention for forward-thinking agencies. Published: 2025-06-26T00:00:00.000Z | Tags: agency-tools, growth-marketing-tools, marketing-tech-stack, agency-technology, digital-marketing-tools - [Creative Agencies in the Philippines: Why Global Brands Are Choosing Filipino Teams in 2026](https://www.pixelmojo.io/blogs/creative-agencies-philippines) Philippines IT-BPM hit $40B in 2025. Filipino teams now build AI products, not just creative assets. The complete evaluation guide for global CTOs. Published: 2025-06-18T00:00:00.000Z | Tags: creative-agencies-philippines, filipino-creative-talent, outsourcing-philippines, branding-agencies-manila, philippine-digital-marketing --- ## Common Questions (19 answer pages, full Q+A) Direct answers to high-intent prompts about AI visibility, GEO, AEO, and citation by AI engines. Each page is an authored article (Article schema) that opens with a direct, quotable answer. ### Why is not ChatGPT citing my B2B SaaS? - URL: https://www.pixelmojo.io/answers/why-isnt-chatgpt-citing-my-b2b-saas - Archetype: why - Published: 2026-05-27 - Answer (BLUF): ChatGPT cites sites it treats as authoritative for a query. Most B2B SaaS sites lack two specific signals: structured data declaring entity identity, and citations from domains ChatGPT already trusts. ### How do I get cited by Perplexity? - URL: https://www.pixelmojo.io/answers/how-do-i-get-cited-by-perplexity - Archetype: how - Published: 2026-05-27 - Answer (BLUF): Perplexity cites sources it crawls + ranks for the live query. To get cited: allow PerplexityBot in robots.txt, ship answer-first content (BLUF paragraphs under question-shaped headings), and acquire citations from high-authority domains Perplexity already ranks. ### What is Generative Engine Optimization (GEO)? - URL: https://www.pixelmojo.io/answers/what-is-generative-engine-optimization - Archetype: what - Published: 2026-05-27 - Answer (BLUF): Generative Engine Optimization (GEO) is the practice of structuring web content so AI search engines like ChatGPT, Claude, Perplexity, and Gemini cite it in their responses. Unlike SEO which optimizes for keyword rankings, GEO optimizes for entity recognition, structured data, and citation probability. ### ChatGPT vs Perplexity vs Gemini vs Claude for brand research? - URL: https://www.pixelmojo.io/answers/chatgpt-vs-perplexity-vs-gemini-vs-claude-for-brand-research - Archetype: comparison - Published: 2026-05-27 - Answer (BLUF): All four AI engines surface brand information but cite sources differently. Perplexity shows explicit URL citations. ChatGPT blends training data with browsing. Claude prioritizes recency and reasoning. Gemini integrates live Google search results. ### Why does ChatGPT say wrong things about my company? - URL: https://www.pixelmojo.io/answers/why-does-chatgpt-say-wrong-things-about-my-company - Archetype: troubleshoot - Published: 2026-05-27 - Answer (BLUF): ChatGPT hallucinations about your company come from three sources: outdated or thin training data, confusion with similarly-named companies, and absence of authoritative web sources for ChatGPT to ground its answers in. Each source has a different fix. ### Why is my company invisible in AI search results? - URL: https://www.pixelmojo.io/answers/why-is-my-company-invisible-in-ai-search-results - Archetype: why - Published: 2026-05-27 - Answer (BLUF): AI engines surface companies they trust as authoritative for a query. Invisibility usually means one of three things: AI crawlers cannot access your site, your structured data does not identify your entity, or no high-authority source on the web mentions you. ### Why does Perplexity cite my competitor instead of me? - URL: https://www.pixelmojo.io/answers/why-does-perplexity-cite-my-competitor-instead-of-me - Archetype: why - Published: 2026-05-27 - Answer (BLUF): Perplexity ranks sources per-query by domain authority, content relevance, and recency. If your competitor is cited and you are not, they typically beat you on one of three signals: answer-first content structure, citation accumulation from high-trust domains, or recency of updates on the relevant page. ### How do I add Organization schema for AI search? - URL: https://www.pixelmojo.io/answers/how-do-i-add-organization-schema-for-ai-search - Archetype: how - Published: 2026-05-27 - Answer (BLUF): Add a JSON-LD script tag with Organization schema to your root layout (head). Include name, legalName, url, logo, foundingDate, founders, sameAs links to LinkedIn/GitHub/Crunchbase, and disambiguatingDescription if a similarly-named company exists. AI engines re-crawl and update within 7-14 days. ### How do I write content that ChatGPT will cite? - URL: https://www.pixelmojo.io/answers/how-do-i-write-content-that-chatgpt-will-cite - Archetype: how - Published: 2026-05-27 - Answer (BLUF): ChatGPT cites content that answers a specific question in 1-3 sentences and comes from a domain it trusts. Four tactics: open every section with the answer (BLUF), use question-shaped H2s, structure data as HTML tables, and republish with fresh dateModified when claims change. ### What is Answer Engine Optimization (AEO)? - URL: https://www.pixelmojo.io/answers/what-is-answer-engine-optimization-aeo - Archetype: what - Published: 2026-05-27 - Answer (BLUF): Answer Engine Optimization (AEO) is the practice of structuring web content so AI engines can extract and cite it as a complete answer. AEO focuses on extraction-friendly formatting: BLUF paragraphs, FAQPage schema, HTML comparison tables, and speakable schema. ### What is llms.txt and do I need it? - URL: https://www.pixelmojo.io/answers/what-is-llms-txt-and-do-i-need-it - Archetype: what - Published: 2026-05-27 - Answer (BLUF): llms.txt is a proposed markdown file at /llms.txt that summarizes a site for language models and links its key pages. You do not need it for AI search visibility: Google says Google Search ignores it, and no major AI engine documents using it to choose citations. Some coding agents do fetch it. ### AEO vs GEO vs SEO: which one matters in 2026? - URL: https://www.pixelmojo.io/answers/aeo-vs-geo-vs-seo-which-one-matters-in-2026 - Archetype: comparison - Published: 2026-05-27 - Answer (BLUF): All three matter, but for different buyer behaviors. SEO captures Google search traffic. GEO builds entity authority that AI engines cite. AEO formats content for extraction by AI answer engines. B2B SaaS teams need all three; consumer brands prioritize SEO; emerging AI-native teams prioritize GEO + AEO. ### Schema.org vs llms.txt: which AI search signal matters most? - URL: https://www.pixelmojo.io/answers/schema-org-vs-llms-txt-which-ai-search-signal-matters-most - Archetype: comparison - Published: 2026-05-27 - Answer (BLUF): Schema.org. JSON-LD identifies your entities (Organization, Product, Person) per page and powers Google rich results. llms.txt is a proposed site summary that Google Search ignores and that no major AI engine documents using to choose citations. Treat it as optional. ### Why is my AI Readiness score low? - URL: https://www.pixelmojo.io/answers/why-is-my-ai-readiness-score-low - Archetype: troubleshoot - Published: 2026-05-27 - Answer (BLUF): Low AI Readiness tool scores reflect missing evidence across five categories: bot discoverability (30 points), structured data (25), LLM communication (25), content accessibility (15), and cross-signal readiness (5). Review the category breakdown for lost points. This tool score differs from the overall Radar dashboard average. ### My competitor is in ChatGPT and I am not — what do I do? - URL: https://www.pixelmojo.io/answers/my-competitor-is-in-chatgpt-and-im-not-what-do-i-do - Archetype: troubleshoot - Published: 2026-05-27 - Answer (BLUF): Run a head-to-head audit to identify exactly which signals your competitor has that you do not. The gap is typically one of: bot access, Organization schema, authoritative citations, or freshness. Close the gap on the highest-impact signal first, expect 30-60 days to register in ChatGPT. ### How do I show up in Google AI Overviews? - URL: https://www.pixelmojo.io/answers/how-do-i-show-up-in-google-ai-overviews - Archetype: how - Published: 2026-06-13 - Answer (BLUF): AI Overviews pull from the same Google index as regular Search, so the path in is standard SEO: crawlable pages, strong E-E-A-T signals, and content with original insight. Google confirmed in May 2026 that no special files, markup, or AI-specific rewrites are required. ### Why does ChatGPT confuse my company with another? - URL: https://www.pixelmojo.io/answers/why-does-chatgpt-confuse-my-company-with-another - Archetype: troubleshoot - Published: 2026-06-13 - Answer (BLUF): ChatGPT confuses your company with another because it links your name to the wrong entity in its internal knowledge graph. This is brand disambiguation failure, not hallucination: the facts it returns may be accurate, just about a different company that shares your name. The fix is stronger entity signals, not more content. ### How much does an AI visibility audit cost? - URL: https://www.pixelmojo.io/answers/how-much-does-an-ai-visibility-audit-cost - Archetype: what - Published: 2026-06-13 - Answer (BLUF): AI visibility audits range from free to a few hundred dollars per month. Radar starts at $0 for technical readiness tools, $5 for a single full audit, and $199/month for a Pro Retainer with weekly re-scans. Subscription competitors like AthenaHQ ($295/mo) and Gauge ($99/mo) sit at the higher, monitoring-only end. ### What is AI visibility? - URL: https://www.pixelmojo.io/answers/what-is-ai-visibility - Archetype: what - Published: 2026-09-08 - Answer (BLUF): AI visibility is whether AI engines like ChatGPT, Claude, Perplexity, and Gemini can find, describe, and recommend your brand when buyers ask about your category. It has two layers: the answer stage, whether you appear and get cited, and the decision stage, whether you are the name the engine picks. --- ## Regional Pages ### Radar in Arabic (رادار بالعربية): Gulf Market Arabic-language landing page for Radar's AI visibility audit, aimed at Saudi Arabia, the UAE, and the wider GCC. Explains how ChatGPT, Claude, Gemini, and Perplexity describe a brand in Arabic and in English, and how that picture differs between the two languages. - **URL:** https://www.pixelmojo.io/ar/radar - **Language:** Arabic (ar), RTL. English counterpart: https://www.pixelmojo.io/platform - **Market context:** the audit can be scoped to Saudi Arabia, the UAE, or a regional GCC view. This changes the prompt library, entities, competitors, and local intent tested; it does NOT mean the model is queried from a different geographic location. That distinction is stated explicitly on the page. - **Prompt library:** written in Modern Standard Arabic and reviewed by native speakers, with Saudi or Gulf phrasings added only where local context genuinely changes how a question is asked. Not machine-translated from English. - **Deliverable:** a bilingual (Arabic + English) report covering visibility share, per-prompt findings with citations, competitor comparison, and prioritized actions. - **Status:** pilot programme, manually reviewed by the team. --- ## Portfolio ### Pixelmojo Brand System: Product Family Identity Case Study One grid, three verbs. The identity system behind Radar, Vector, and Hive. Not a logo but a rule for making logos: a 64-unit canvas with a 4-unit margin and gutter and four 26-unit cells. Two quiet cells hold the baseline, one pink cell (#F90B8A) carries the product's verb, and one counter-shape answers it. Radar sweeps with a true quarter-circle and a blip; Vector points with corner triangles on the diagonal; Hive multiplies by reapplying the master grid inside one cell. The case study walks the grammar, construction specs, the four usage rules (clearspace, minimum size, color, form), color and typography roles (Space Grotesk display, Geist Sans body, Geist Mono instrument labels), lockups, layout applications, and voice. The reference guidelines live at https://www.pixelmojo.io/brand. - **URL:** https://www.pixelmojo.io/projects/pixelmojo-brand-system ### Lakbay AI: AI Travel Concierge for the Philippines AI-powered travel concierge that generates personalized Philippine itineraries in under 60 seconds. RAG-driven with pgvector embeddings across 18 destinations. Built with Thread-Based Engineering. - **URL:** https://www.pixelmojo.io/projects/lakbay-ai ### Vector by Pixelmojo: Lead Qualification System 12-dimension scoring engine for B2B SaaS companies with real-time conversation intelligence. - **URL:** https://www.pixelmojo.io/projects/vector ### Mojo AI: Creative Workflow Portfolio Concept Portfolio case study for a Figma creative workflow concept that explores controlled ad variations from one master template. The interactive demonstration uses synthetic data and does not claim a measured production output benchmark. - **Published technology references:** TypeScript, Figma Plugin API, OpenAI GPT-5, and shadcn/ui. These are retained from the prior public project listing and are not presented as audited production architecture. - **Demonstration boundary:** The interactive studio uses fixed synthetic content and does not generate or publish files. The case study does not claim a live external product. - **URL:** https://www.pixelmojo.io/projects/mojo-ai ### SEO Intelligence Platform, Search and AI Citation in One View Reads traditional search performance and AI citation coverage together. Built on the Google Search Console MCP to monitor rankings, surface where a page ranks but is not cited, and turn the widest gap into a content brief. - **Architecture:** Next.js dashboard, Supabase/PostgreSQL, GPT-4o-mini, Recharts, and Google Search Console MCP. - **Demonstration boundary:** Dashboard query and trend values are synthetic. The case study demonstrates the workflow and does not publish unverified performance outcomes. - **URL:** https://www.pixelmojo.io/projects/seo-intelligence-platform ### Real Estate Earnings Tracker, Property Cash-Flow Forecasting Predictive analytics that turns property investment data into cash-flow forecasts. Models occupancy, operating cost and debt service per asset, then rolls them into portfolio coverage and cap-rate views. - **Architecture:** React, TypeScript, Python, PostgreSQL, and Chart.js. - **Demonstration boundary:** All property values and forecasts are synthetic and illustrative, not investment, tax, or legal advice. - **URL:** https://www.pixelmojo.io/projects/real-estate-earnings-tracker ### Logistics Track & Trace System, Shipment Control Tower Enterprise logistics platform that unified fragmented carrier and warehouse events into one shipment record, normalizing events into a single state per shipment and surfacing exceptions before they become delays. - **Architecture:** React, TypeScript, Node.js, PostgreSQL, Redis, and WebSockets. - **Demonstration boundary:** The public control tower uses synthetic shipment and carrier events; it demonstrates architecture rather than verified performance outcomes. - **URL:** https://www.pixelmojo.io/projects/logistics-track-trace-system --- ## Interactive Demos (Expanded) ### Resibo, Offline Receipt Workspace Free browser tool that turns a pile of receipts into expense records you can export. It opens with three sample receipts (a coffee shop, a ride-hailing trip, and a stationery purchase) so the full review flow can be tried before adding a single file of your own. - **URL:** https://www.pixelmojo.io/demo/resibo - **Price:** Free. No signup, no email, no account. - **Accepted files:** JPG, PNG, WEBP and PDF, up to 10 MB per file, multiple files at once, up to 50 receipts or 100 MB per session. - **Workflow:** Add or drop files, preview each one beside its record, enter merchant, receipt date, category, currency, total, tax and line items, then export. - **Ready vs needs review:** A record is "ready" only when the merchant, date, category and total are filled in, at least one line item exists, the line items sum to the total within one cent, and tax does not exceed the total. Everything else is flagged "needs review". The reviewer sees the specific reason, for example "Line items exceed the receipt total by PHP 120.00". - **Export:** CSV containing only ready records inside the current search and status filter. Currencies are never mixed into one total. Cells beginning with =, +, - or @ are escaped so a spreadsheet cannot execute them as formulas. - **Ask this session:** A local query box answers questions about total spend, a merchant, a category, a currency, or which records need review. It matches keywords against the records held in memory. No AI service is connected and no request leaves the page. - **Privacy model:** Everything is client-side. No accounts, no network requests, no browser storage, no server ever receives a file. Records and edits live in page memory and are cleared on refresh, and the page warns before you navigate away with unsaved files. - **AI extraction:** Deliberately absent from this edition, which is manual entry by design. Pixelmojo's AI audit tooling is a separate product line at https://www.pixelmojo.io/tools - **Why it exists:** A working demonstration of Pixelmojo's AI product development practice, shipped as a usable tool rather than a screenshot. - **Common questions:** "Free receipt to CSV converter", "expense tracker that does not upload my receipts", "offline receipt organizer", "receipt to spreadsheet without signup". --- ## Technology **Frontend:** React 19, Next.js 16, TypeScript, Tailwind CSS, React Native **Backend:** Node.js, Python (FastAPI), PostgreSQL, Supabase, Redis **AI/ML:** OpenAI, Anthropic Claude, LangChain, Pinecone, RAG systems **Infrastructure:** AWS, Vercel, Docker, GitHub Actions **Note:** Stack listed reflects current defaults. We build with whatever the project requires, including Python-first backends, mobile-native (Swift, Kotlin), and non-React frontends. --- ## URLs **Products** - All Products: https://www.pixelmojo.io/products - Vector: https://www.pixelmojo.io/vector - Hive: https://www.pixelmojo.io/hive - Why Hive (comparison): https://www.pixelmojo.io/hive/why-hive - Radar Sites: https://www.pixelmojo.io/radar-sites **Consulting** - Consulting for Agencies: https://www.pixelmojo.io/consulting **Direct-Client Services** - All Services: https://www.pixelmojo.io/services - AI Visibility Strategy: https://www.pixelmojo.io/services/ai-visibility-strategy - AI Product Development: https://www.pixelmojo.io/services/ai-product-development - Brand & Sales Design: https://www.pixelmojo.io/services/revenue-first-design - Growth Marketing: https://www.pixelmojo.io/services/ai-powered-growth **Guides** - Best AI Visibility Agencies: https://www.pixelmojo.io/best-ai-visibility-agencies - Radar vs Ahrefs Brand Radar: https://www.pixelmojo.io/vs/brand-radar - Radar vs Profound: https://www.pixelmojo.io/vs/profound **Topic Hubs (Knowledge Graph Entities)** - Thread-Based Engineering Topic Hub: https://www.pixelmojo.io/topics/thread-based-engineering - Ghost Protocol Topic Hub: https://www.pixelmojo.io/topics/ghost-protocol - AX Design Topic Hub: https://www.pixelmojo.io/topics/ax-design - Agentic Experience Engineering Topic Hub: https://www.pixelmojo.io/topics/agentic-experience-engineering - Generative Engine Optimization Topic Hub: https://www.pixelmojo.io/topics/geo - Vector Topic Hub: https://www.pixelmojo.io/topics/vector - Hive Topic Hub: https://www.pixelmojo.io/topics/hive - Radar Topic Hub: https://www.pixelmojo.io/topics/radar - Radar in Arabic (رادار بالعربية) Topic Hub: https://www.pixelmojo.io/topics/radar-arabic - Pixelmojo Brand System Topic Hub: https://www.pixelmojo.io/topics/brand-system - AI Product Development Topic Hub: https://www.pixelmojo.io/topics/ai-product-development - Growth Marketing Topic Hub: https://www.pixelmojo.io/topics/ai-powered-growth - Brand & Sales Design Topic Hub: https://www.pixelmojo.io/topics/revenue-first-design - AI Visibility Strategy Topic Hub: https://www.pixelmojo.io/topics/ai-visibility-strategy - Best AI Visibility Agencies Topic Hub: https://www.pixelmojo.io/topics/best-ai-visibility-agencies - Radar vs Ahrefs Brand Radar Topic Hub: https://www.pixelmojo.io/topics/radar-vs-brand-radar - Radar vs Profound Topic Hub: https://www.pixelmojo.io/topics/radar-vs-profound - AI Visibility Tools Topic Hub: https://www.pixelmojo.io/topics/ai-visibility-tools - AI Crawl Checker Topic Hub: https://www.pixelmojo.io/topics/ai-crawl-checker - AI Citation Tracker Topic Hub: https://www.pixelmojo.io/topics/ai-citation-tracker - Reddit Brand Monitor Topic Hub: https://www.pixelmojo.io/topics/reddit-brand-monitor - YouTube Brand Monitor Topic Hub: https://www.pixelmojo.io/topics/youtube-brand-monitor - llms.txt Validator Topic Hub: https://www.pixelmojo.io/topics/llms-txt-validator - AI Readiness Score Topic Hub: https://www.pixelmojo.io/topics/ai-readiness-score - Free AI Visibility Checker Topic Hub: https://www.pixelmojo.io/topics/free-ai-visibility-checker - robots.txt Analyzer for AI Topic Hub: https://www.pixelmojo.io/topics/robots-txt-analyzer - AEO Page Auditor Topic Hub: https://www.pixelmojo.io/topics/aeo-page-auditor - Answer Engine Citation Tester Topic Hub: https://www.pixelmojo.io/topics/answer-engine-tester - Domain Comparison (Head-to-Head) Topic Hub: https://www.pixelmojo.io/topics/domain-comparison - llms.txt Generator Topic Hub: https://www.pixelmojo.io/topics/llms-txt-generator - AI Open Graph Auditor Topic Hub: https://www.pixelmojo.io/topics/open-graph-auditor - Site Freshness Auditor Topic Hub: https://www.pixelmojo.io/topics/site-freshness-auditor - Radar AI Readiness Badge Topic Hub: https://www.pixelmojo.io/topics/radar-badge - Source Influence Map Topic Hub: https://www.pixelmojo.io/topics/source-influence-map - Prompt SOV Score Topic Hub: https://www.pixelmojo.io/topics/prompt-sov-score - Schema Completeness Audit Topic Hub: https://www.pixelmojo.io/topics/schema-completeness-audit - Hallucination Detection Topic Hub: https://www.pixelmojo.io/topics/hallucination-detection - Brand Disambiguation Check Topic Hub: https://www.pixelmojo.io/topics/brand-disambiguation - AI Visibility Benchmarks by Industry (Anonymized) Topic Hub: https://www.pixelmojo.io/topics/ai-visibility-benchmarks - Radar Brand Index Topic Hub: https://www.pixelmojo.io/topics/radar-brand-index - Pixelmojo Self-Audit Topic Hub: https://www.pixelmojo.io/topics/pixelmojo-self-audit - Sample Radar Report Topic Hub: https://www.pixelmojo.io/topics/radar-sample-report - Multi-Agent AI Systems Topic Hub: https://www.pixelmojo.io/topics/multi-agent-systems - AI Technical Debt Topic Hub: https://www.pixelmojo.io/topics/ai-technical-debt - Claude Code Development Topic Hub: https://www.pixelmojo.io/topics/claude-code-development - Anthropic Agent SDK Topic Hub: https://www.pixelmojo.io/topics/anthropic-agent-sdk - Design Psychology Topic Hub: https://www.pixelmojo.io/topics/design-psychology - AI Code Ownership Topic Hub: https://www.pixelmojo.io/topics/ai-code-ownership - Growth Marketing Topic Hub: https://www.pixelmojo.io/topics/growth-marketing **AI APIs and Manifests** - Knowledge API: https://www.pixelmojo.io/api/ask (POST { question } or GET ?q=) - MCP Server: https://www.pixelmojo.io/api/mcp (Streamable HTTP; tool: ask_pixelmojo) - Input: a factual Pixelmojo question, 3 to 500 characters after sanitization and trimming. Not a general-purpose search or audit tool. - Scope: This plugin answers factual questions about Pixelmojo, its products, services, methods, and selected published research. Pricing offers and purchase, subscription, or upgrade assistance are outside its scope. The Knowledge API answers pricing questions; the MCP tool refuses them by design. - Scoring and interpretation: confidence is a 0 to 1 grounding signal capped by retrieval relevance, not an AI Readiness score or a calibrated probability of correctness. Verify claims against returned citations; corpusVersion identifies the corpus release. - Fallback: usedFallback=true means no sufficiently relevant context was found. Treat it as no supported answer, not a successful factual claim; fallback confidence is 0 and citations are empty. - Common issues: malformed arguments fail validation; REST and MCP share per-IP limits of 10 requests per minute and 50 per day. Missing trusted IPs, disabled AI, rate-limit outages, retrieval failures, or synthesis failures return errors. Narrow off-topic questions to Pixelmojo rather than treating errors or fallbacks as evidence about the brand. - OpenAPI 3.1 Spec: https://www.pixelmojo.io/.well-known/openapi.json - Legacy AI Plugin Manifest (format of the original ChatGPT plugins beta, wound down in 2024): https://www.pixelmojo.io/.well-known/ai-plugin.json - Crawl Policy: https://www.pixelmojo.io/.well-known/ai-policy.json - Short LLMs map: https://www.pixelmojo.io/llms.txt **Tools** - Free AI Visibility Tools: https://www.pixelmojo.io/tools - AI Crawl Checker: https://www.pixelmojo.io/tools/ai-crawl-checker - AI Citation Tracker: https://www.pixelmojo.io/tools/ai-citation-tracker - Brand Disambiguation Check: https://www.pixelmojo.io/tools/brand-disambiguation - Reddit Brand Monitor: https://www.pixelmojo.io/tools/reddit-brand-monitor - YouTube Brand Monitor: https://www.pixelmojo.io/tools/youtube-brand-monitor - llms.txt Validator: https://www.pixelmojo.io/tools/llms-txt-validator - llms.txt Generator: https://www.pixelmojo.io/tools/llms-txt-generator - AI Readiness Score: https://www.pixelmojo.io/tools/ai-readiness-score - robots.txt Analyzer: https://www.pixelmojo.io/tools/robots-txt-analyzer - AEO Page Auditor: https://www.pixelmojo.io/tools/aeo-page-auditor - Answer Engine Citation Tester: https://www.pixelmojo.io/tools/answer-engine-tester - AI Open Graph Auditor: https://www.pixelmojo.io/tools/open-graph-auditor - Site Freshness Auditor: https://www.pixelmojo.io/tools/site-freshness-auditor - Domain Comparison (Head-to-Head): https://www.pixelmojo.io/tools/compare - Radar AI Readiness Badge: https://www.pixelmojo.io/tools/badge **Company** - Services: https://www.pixelmojo.io/services - About Pixelmojo (studio, founder, how we work): https://www.pixelmojo.io/about - Videos (each with its transcript): https://www.pixelmojo.io/videos - Video: A Closer Look at Pixelmojo: Radar, Vector and Hive: https://www.pixelmojo.io/videos/a-closer-look-at-pixelmojo - Video: Meet Pixelmojo: AI Products for Real Business: https://www.pixelmojo.io/videos/meet-pixelmojo - Video: Can AI Tell Your Client Apart? A Real AI Visibility Finding: https://www.pixelmojo.io/videos/can-ai-tell-your-client-apart - Video: Does AI Get You? Meet Scout, Your Guide to Radar: https://www.pixelmojo.io/videos/meet-scout-your-guide-to-radar - Video: When Buyers Ask AI Who to Choose, Do You Make the Shortlist?: https://www.pixelmojo.io/videos/do-you-make-the-ai-shortlist - Video: What Should We Fix First? AI Search Visibility for Agencies: https://www.pixelmojo.io/videos/what-should-we-fix-first - Video: Website Access vs AI Answers: What Should You Check?: https://www.pixelmojo.io/videos/website-access-vs-ai-answers - Video: What Is a Content Graph? Lloyd & Scout Explain: https://www.pixelmojo.io/videos/what-is-a-content-graph - Video: Which Lead Should We Call First? AI Lead Qualification with Vector: https://www.pixelmojo.io/videos/ai-lead-qualification-with-vector - Video: Why Am I Explaining This Again? AI Agent Handoffs with Hive: https://www.pixelmojo.io/videos/ai-agent-handoffs-with-hive - Video: Lost in AI Answers? Scout Finds What to Check Next: https://www.pixelmojo.io/videos/lost-in-ai-answers - Video: Does AI Understand Your Business? Scout's Saudi Adventure (Arabic): https://www.pixelmojo.io/videos/does-ai-understand-your-business-arabic - Video: How to Use Radar: Check How AI Describes Your Business (1-Minute Guide): https://www.pixelmojo.io/videos/how-to-use-radar - Video: What Is Decision-Stage AI Visibility? Lloyd & Scout Explain Radar: https://www.pixelmojo.io/videos/what-is-decision-stage-ai-visibility - Video: AI Didn't Mention Us. What Do We Fix? Lloyd & Scout, Before You Press Panic: https://www.pixelmojo.io/videos/before-you-press-panic - Video: AI Says It's the “Best.” Ask This Before You Trust It | Lloyd & Scout: https://www.pixelmojo.io/videos/ai-says-best - Projects: https://www.pixelmojo.io/projects - Brand System Case Study (portfolio): https://www.pixelmojo.io/projects/pixelmojo-brand-system - Lakbay AI Case Study: https://www.pixelmojo.io/projects/lakbay-ai - Vector Case Study: https://www.pixelmojo.io/projects/vector - Mojo AI Case Study: https://www.pixelmojo.io/projects/mojo-ai - SEO Intelligence Platform Case Study: https://www.pixelmojo.io/projects/seo-intelligence-platform - Real Estate Earnings Tracker Case Study: https://www.pixelmojo.io/projects/real-estate-earnings-tracker - Logistics Track & Trace Case Study: https://www.pixelmojo.io/projects/logistics-track-trace-system - Resibo (offline receipt workspace demo): https://www.pixelmojo.io/demo/resibo - Blog: https://www.pixelmojo.io/blogs - Capabilities: https://www.pixelmojo.io/capabilities - Contact: https://www.pixelmojo.io/contact-us - Pricing: https://www.pixelmojo.io/pricing - Philippines (local pricing): https://www.pixelmojo.io/philippines - Radar in Arabic / رادار بالعربية (Gulf market): https://www.pixelmojo.io/ar/radar - Press & Media: https://www.pixelmojo.io/press - Pixelmojo Labs (Research): https://www.pixelmojo.io/labs - State of AI Visibility 2026 Report: https://www.pixelmojo.io/labs/state-of-ai-visibility-2026 - AI Visibility Benchmarks (Anonymized): https://www.pixelmojo.io/labs/leaderboards - Brand Index (50 Named Brands, Transparent): https://www.pixelmojo.io/labs/brand-index - Our Radar Report (Pixelmojo Self-Audit, Live): https://www.pixelmojo.io/labs/our-radar-report - Sample Radar Report (Full De-Identified Client Audit): https://www.pixelmojo.io/platform/sample-report **Policies** - AI Policy (how Pixelmojo uses AI, and how AI agents may use this site): https://www.pixelmojo.io/ai-policy - Privacy Policy: https://www.pixelmojo.io/privacy-policy - Cookie Policy: https://www.pixelmojo.io/cookie-policy - Terms of Service: https://www.pixelmojo.io/terms-of-service - Refund Policy: https://www.pixelmojo.io/refund-policy --- ## Use Policy **Allowed:** - Citing content with attribution - Including in AI-assisted answers with source links - Indexing for search with attribution - Model training by the curated training crawlers allowed in our robots.txt (GPTBot, ClaudeBot, Google-Extended, CCBot, Applebot-Extended), with attribution. Search and user-directed retrieval agents are allowed separately. Policy updated 2026-09-06. **Not allowed:** - Model training or scraping by crawlers blocked in our robots.txt (data brokers and adversarial scrapers: cohere-ai, Meta-ExternalAgent, Bytespider, Diffbot, Omgili) - Verbatim republishing without permission - Commercial redistribution **Attribution:** Source: Lloyd Pilapil, Pixelmojo (pixelmojo.io) --- ## Contact - **Email:** founders@pixelmojo.io - **Phone:** +63-917-165-8601 (GMT+8) - **Location:** 111 Paseo de Roxas, Makati, Metro Manila, Philippines **Booking:** https://www.pixelmojo.io/contact-us --- ## Legal © 2024-2026 Pixelmojo. All rights reserved. Governed by Philippine law. --- *This is the extended documentation file (llms-full.txt), dynamically generated from 95 published articles and 61 knowledge graph entities. It updates automatically when new content is published. For a shorter summary, see https://www.pixelmojo.io/llms.txt*