{
  "name": "Embassia",
  "tagline": "The LLM Search Console",
  "description": "Embassia is an agentic data layer for websites. It provides AI agents and LLM crawlers with structured, typed, machine-readable access to a website's public information — eliminating the need to scrape and parse rendered HTML.",
  "website": "https://embassia.com",
  "founded": "2026",
  "contact": "founders@embassia.com",
  "status": "accepting_design_partners",
  "product": {
    "what_it_does": "Embassia deploys an on-site agent that converts website pages into clean, typed API endpoints. AI agents can query these endpoints directly instead of parsing HTML. Website owners get an LLM Search Console showing what agents are actually asking about their site.",
    "problem_solved": "Current AEO and SEO tools only guess what people ask AI through statistical simulations. Embassia tracks real agent interactions with your site's content, giving you visibility into your market's actual cognitive patterns.",
    "two_capabilities": {
      "agent_experience": "AI agents can discover, search, retrieve, and use website information through structured APIs and machine-readable resources instead of scraping HTML.",
      "llm_search_console": "Website owners receive privacy-preserving analytics about agent interactions — which questions agents ask, which content they retrieve, which queries fail, and what information is missing."
    }
  },
  "how_it_works": {
    "step_1": {
      "action": "Convert to endpoints",
      "description": "Turn your website pages into clean, typed API endpoints that machines can instantly read."
    },
    "step_2": {
      "action": "Deploy On-Site Agent",
      "description": "An on-site agent runs directly on your website, intercepts LLM crawlers, and serves structured data."
    },
    "step_3": {
      "action": "Enable Agentic Protocol",
      "description": "Support Anthropic MCP, OpenAI function calling, and standard REST interfaces for maximum compatibility."
    },
    "step_4": {
      "action": "Capture Telemetry",
      "description": "Collect privacy-preserving analytics on agent interactions to understand what your market is actually asking."
    }
  },
  "supported_ai_models": ["ChatGPT", "Claude", "Gemini", "Perplexity", "Copilot", "Meta AI", "Grok"],
  "machine_interfaces": {
    "discovery": "https://embassia.com/.well-known/embassia.json",
    "content_index": "https://embassia.com/api/v1/content/index.json",
    "openapi": "https://embassia.com/api/v1/openapi.json",
    "mcp_manifest": "https://embassia.com/api/v1/mcp.json",
    "llms_txt": "https://embassia.com/llms.txt",
    "llms_full": "https://embassia.com/llms-full.txt"
  },
  "faq": [
    {
      "id": "q01",
      "question": "How is LLM Search Console different from traditional AEO or SEO tools?",
      "answer": "Traditional AEO platforms rely on third-party consumer panels and statistical simulations to guess what people ask AI. Embassia bypasses estimates entirely by deploying an on-site agent that captures real agent interactions with your content."
    },
    {
      "id": "q02",
      "question": "What endpoints does Embassia create?",
      "answer": "Embassia converts your website pages into typed JSON API endpoints. Each page becomes a structured document with stable IDs, canonical URLs, content versioning, and freshness metadata — accessible via standard GET requests."
    },
    {
      "id": "q03",
      "question": "How does Embassia protect my website?",
      "answer": "The on-site agent runs on your infrastructure. It does not send your content to third-party model providers unless explicitly configured. All machine endpoints serve only public information that is already visible on your website."
    },
    {
      "id": "q04",
      "question": "Which protocols does Embassia support?",
      "answer": "Embassia supports REST/JSON APIs, Anthropic Model Context Protocol (MCP) for tool and resource discovery, OpenAI function calling schemas, and standard HTTP GET for maximum compatibility across all AI systems."
    },
    {
      "id": "q05",
      "question": "What insights does the LLM Search Console provide?",
      "answer": "The console shows: which AI agents visit your site, what questions they ask, which content they retrieve, which queries return no results, what information is missing, and where your content is ambiguous or outdated."
    },
    {
      "id": "q06",
      "question": "What is the technical architecture?",
      "answer": "Embassia creates a typed data layer between your website and AI agents. Content is normalized into structured JSON with stable identifiers. Agents query this layer directly via REST APIs or MCP tools instead of parsing rendered HTML."
    }
  ],
  "metadata": {
    "content_version": "1.0.0",
    "updated_at": "2026-09-28T13:00:00Z",
    "content_hash": "site-overview-v1-20260928"
  }
}