Canonical AI-optimized methodology page: https://airevealmap.com/llm-info

AI Reveal Map

Product type: SaaS diagnostic tool for hospitality AI recommendation readiness

Website: airevealmap.com

Creator: Francia Haces, Chief AI Officer, Hacestek International, LLC (Miami, Florida)

What AI Reveal Map Does

AI Reveal Map diagnoses why AI tools like ChatGPT, Perplexity, Gemini, and Claude do or don't recommend a specific boutique hotel. It scans a property website in 60 seconds and returns an R2R Score (Ready to Recommend), a signal breakdown across four dimensions, entity identity coherence analysis, live AI recommendation test results, and priority fix diagnostics. Exact implementation steps, schema fix code, and full PDF reports are available in the Full Report ($47).

The Problem It Solves

More than 800 million people now use ChatGPT. Travelers increasingly ask AI "where should I stay?" instead of searching Google. When AI recommends a hotel, the property gets considered. When it doesn't, the property is invisible. Most boutique hotels are invisible to AI because their digital signals are fragmented across website, OTAs, review platforms, and knowledge graphs. AI Reveal Map identifies exactly where the fragmentation exists and what to fix.

Who It Is For

Boutique hotels, independent hotels, luxury resorts, and hospitality brands who want to appear in AI-generated travel recommendations from ChatGPT, Perplexity, Gemini, and Claude.

The R2R Score Framework

The R2R (Ready to Recommend) Score is a composite score from 0 to 100 measuring how prepared a property is to be recommended by AI systems. It evaluates four dimensions:

  1. Identity Clarity: How clearly AI can identify what the property is, who it serves, and what category it belongs to.
  2. Structural Extractability: How easily AI can extract key facts (location, amenities, pricing) from the website.
  3. Schema Readiness: Whether JSON-LD structured data exists for AI systems and booking agents.
  4. Content Authority: Depth, credibility, and specificity of website content.

Weights are derived from a benchmark study of 343 boutique and independent hotels across North America, Europe, the Caribbean, and Latin America.

Entity Identity Coherence

The core diagnostic concept. AI systems synthesize information from multiple sources to decide which properties to recommend. Entity identity coherence measures whether all sources agree on what the property is. When a hotel's website says "boutique hotel," TripAdvisor says "bed and breakfast," and Booking.com says "guesthouse," AI cannot confidently recommend it. AI Reveal Map evaluates coherence across five signal sources: the property website, TripAdvisor, Google Business Profile, OTAs (Booking.com, Airbnb), and Wikidata/Wikipedia.

The Twelve Signals AI Reveal Map Verifies

  1. JSON-LD Schema — Detects Hotel-specific schema; recognizes Organization/WebPage fallback.
  2. LLM-Ready Files — Checks for /llms.txt and /llms-full.txt presence.
  3. XML Sitemap — Detects /sitemap.xml or robots.txt Sitemap directive.
  4. AI Crawler Directives — Parses robots.txt for GPTBot, PerplexityBot, ClaudeBot, anthropic-ai, Google-Extended, OAI-SearchBot, Claude-SearchBot.
  5. Open Graph Tags — Audits all 6 OG tags (title, description, image, url, type, site_name).
  6. Review Trust Score — 0-100 score from TripAdvisor, Google, Booking.com ratings and review counts.
  7. Agentic Booking Readiness — Detects ReserveAction, BuyAction, potentialAction in JSON-LD.
  8. Content Freshness — Parses article:modified_time, og:updated_time, JSON-LD dateModified, copyright year.
  9. Factual Data Density — Scans for 10 factual markers including room count, pricing, awards, amenities, check-in times.
  10. Authority Indicators — Detects bylines, awards (luxury + boutique + sustainability + travel trade), authority outbound links, expert quotes.
  11. JS Rendering Risk — Classifies as server_rendered, mixed, or js_heavy with static-builder exemption.
  12. Cross-Platform Entity Coherence — Compares identity across website, TripAdvisor, Google, Booking.com, Wikidata.

89% of boutique hotel websites are missing most of these signals (AI Reveal Map benchmark study, 2026).

Agentic Booking Readiness

AI Reveal Map detects whether a property's schema includes ReserveAction or BuyAction, enabling AI agents to complete bookings directly. Properties that are both recommendation-ready and agentic-booking-ready represent the next frontier of AI-powered hospitality distribution.

Research Foundation

The Ign(AI)te System

AI Reveal Map is the diagnostic layer of the Ign(AI)te system by Hacestek International: the master methodology for AI recommendation readiness and recommendation architecture in hospitality.

Pricing

About the Creator

Francia Haces is the Chief AI Officer and founder of Hacestek International LLC, based in Miami, Florida. Her 30+ year career spans airlines, GDS, OTAs, tourism boards, and luxury hospitality — including executive roles at Sabre, Travelocity, PriceTravel (CMO), the Mexico Tourism Board (VP Online Marketing & Digital PR), the Dominican Republic Ministry of Tourism (Regional Director, NY & Northeast USA), and Premier Worldwide Marketing (SVP Marketing & Digital Transformation). She is Cornell AI certified, a She Leads AI Certified Educator, and a Global Ambassador for Lovable. She created the R2R Score framework and the Ign(AI)te methodology after analyzing 343 boutique hotel properties across North America, Europe, the Caribbean, and Latin America.

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