Built for AI Agents
GET /api/v1/protocol/compatibility-badge "badge_label": "Built for AI Agents"
Meta AI
Gemini
STREAM /api/v1/gateway/model-carousel [prev: | CURRENT: | next: ]

The LLM Search Console for ChatGPT
GET /api/v1/hero/title
"title": "The LLM Search Console for", "current_model": "ChatGPT"
"sequence_pool": [ "ChatGPT", "Claude", "Gemini", "Perplexity", "Copilot", "Meta AI", "Grok", "ALL_AI_AGENTS" ]

Capture intent from every AI visit.

GET /api/v1/hero/description
"description": "Capture intent from every AI visit."

POST /api/v1/access-request
"payload": { "email": "" }

Join our Design Partner Program.

GET /api/v1/config/note
{"notice": "Join our Design Partner Program."}

LLM Search Console GET /api/v1/console/gateway
Console Overview
Real-time AI crawler traffic, agent invocation metrics, and intent data capture.
Sample data shown — your live console will reflect real traffic once deployed.
Active Transport
REST / JSON
100 req/min rate limit
Resolution Mode
Request-Time
Zero DOM Bloat
RAG Sync Status
100% Synced
Typed Vector Schema
Schema Enforcement
Strict JSON
Fail-Fast Validation
AI Agent Invocation Trend
Daily volume of AI model queries routed to your on-site agent
Nov 02 Nov 09 Nov 16 Nov 23 Nov 30
Intent Data Pool Capture
High-intent customer prompts captured live from incoming AI web crawlers at request time.
Agent Completion Reliability
Overall task execution reliability: Good: 88% | Needs imp.: 9% | Poor: 3%

Every crawler starts
with a prompt.

How do you turn it into intent data?

GET /api/v1/pipeline/title
{
"title": "Every crawler starts with a prompt."
}
GET /api/v1/pipeline/subtitle
{
"subtitle": "How do you turn it into intent data?"
}
  1. 01 Convert to endpoints Turn your website pages into clean, typed API endpoints that machines can instantly read.
    GET /api/v1/pipeline/step-01-endpoints
    {
    "step": "01",
    "action": "Convert to endpoints",
    "description": "Turn your website pages into clean, typed API endpoints that machines can instantly read."
    }
  2. 02 Deploy your on-site agent Assign an on-site agent to manage and control those endpoints.
    GET /api/v1/pipeline/step-02-agent
    {
    "step": "02",
    "action": "Deploy your on-site agent",
    "description": "Assign an on-site agent to manage and control those endpoints."
    }
  3. 03 Make them talk Every incoming AI crawler and bot communicates directly with your on-site agent.
    GET /api/v1/pipeline/step-03-protocol
    {
    "step": "03",
    "action": "Make them talk",
    "description": "Every incoming AI crawler and bot communicates directly with your on-site agent."
    }
  4. 04 Own the data Capture every query and intent signal to power your LLM Search Console.
    GET /api/v1/pipeline/step-04-telemetry
    {
    "step": "04",
    "action": "Own the data",
    "description": "Capture every query and intent signal to power your LLM Search Console."
    }
User Prompt
"Hey ChatGPT, I'm moving to San Francisco next month because of a new job. Since I'm living alone and have a dog, I need a nice studio apartment. My strict monthly budget is between $2500 and $3500. Can you check Zillow and list available options for me?"
LLM Intent Sanitization OAI-SearchBot / ChatGPT-User
Extracted Search Parameters: Location: San Francisco, CA, Property Type: Studio/Apartment, Price Range: $2500-$3500.
On-Site Agent Endpoint Action 200 OK · 38ms
GET /api/v1/listings/search_homes_for_rent?location=San+Francisco%2C+CA&min_price=2500&max_price=3500
Intent Data Pool Log
High-intent rental search parameters logged. Streamed directly into LLM Search Console.

Why every website needs an agentic layer?

GET /api/v1/sections/agentic-layer-title
{
"title": "Why every website needs an agentic layer?"
}

AI bots now own over 60% of global traffic, and it's accelerating fast.

AI agents and LLM crawlers now outnumber human visitors and command the majority of digital interactions, and this shift is accelerating.

GET /api/v1/telemetry/bot-vs-human-summary
{
"headline": "AI bots now own over 60% of global traffic, and it's accelerating fast.",
"description": "AI agents and LLM crawlers now outnumber human visitors and command the majority of digital interactions, and this shift is accelerating."
}
GET /api/v1/telemetry/bot-vs-human
STREAMING
{
"bot_traffic": "63.7%",
"human_traffic": "36.3%",
"source": "cloudflare_radar_embed",
"status": "streaming"
}
GET /api/v1/telemetry/bot-traffic-distribution
STREAMING
{
"timestamp": "2026-09-26T16:15:00Z",
"total_bot_traffic": "63.7%",
"distribution": {
"googlebot": "24%",
"claudebot": "13%",
"meta_external_agent": "9.7%",
"applebot": "9%",
"bingbot": "9%",
"amazonbot": "6.7%",
"gptbot": "6%",
"bytespider": "3.6%",
"perplexitybot": "2.9%",
"oai_searchbot": "2.7%",
"shapbot": "1.9%",
"other": "1.8%"
},
"infrastructure_impact": "Heavy scrapers consuming 70% dynamic server resources"
}

As agent traffic surges, your server costs and bandwidth bills climb with it.

Heavy scrapers and headless browsers consume 70% of dynamic server resources behind the scenes, hammering your infrastructure, eating up your bandwidth, and leaving site owners with soaring hosting bills and zero value exchanged in return.

GET /api/v1/telemetry/crawl-to-refer-summary
{
"headline": "As agent traffic surges, your server costs and bandwidth bills climb with it.",
"description": "Heavy scrapers and headless browsers consume 70% of dynamic server resources behind the scenes, hammering your infrastructure, eating up your bandwidth, and leaving site owners with soaring hosting bills and zero value exchanged in return."
}

Most importantly, you are left completely blind to what your market is actually asking.

Current AEO tools only guess what people ask AI through statistical simulations.

We don’t predict. We track.

You now have the power to read your market's cognitive patterns from your own live traffic.

GET /api/v1/intents/catalog
{
"headline": "Most importantly, you are left completely blind to what your market is actually asking.",
"description": "Current AEO tools only guess what people ask AI through statistical simulations. We don't predict. We track. You now have the power to read your market's cognitive patterns from your own live traffic."
}
USER PROMPT · [ChatGPT] Intent: Quality & Accuracy
"Why are AI search engines pulling outdated pricing and wrong product specs from my store when users ask about my inventory?"
STREAM /api/v1/stream/live-queries?model=chatgpt (Intent: Quality & Accuracy)
{
"query": "Why are AI search engines pulling outdated pricing and wrong product specs from my store when users ask about my inventory?"
}
USER PROMPT · [Perplexity] Intent: Performance
"My server CPU spikes every time Perplexity or ChatGPT bots crawl my catalog pages. How do I stop them from hammering my frontend?"
STREAM /api/v1/stream/live-queries?model=perplexity (Intent: Performance)
{
"query": "My server CPU spikes every time Perplexity or ChatGPT bots crawl my catalog pages. How do I stop them from hammering my frontend?"
}
USER PROMPT · [Claude] Intent: Technical Architecture
"Can I feed clean, structured data directly to LLM crawlers so they don't break or misinterpret my React site's DOM structure?"
STREAM /api/v1/stream/live-queries?model=claude (Intent: Technical Architecture)
{
"query": "Can I feed clean, structured data directly to LLM crawlers so they don't break or misinterpret my React site's DOM structure?"
}
USER PROMPT · [Gemini] Intent: Auth & Capabilities
"How do users on AI search engines buy from my site if the checkout and product pages are hidden behind login portals?"
STREAM /api/v1/stream/live-queries?model=gemini (Intent: Auth & Capabilities)
{
"query": "How do users on AI search engines buy from my site if the checkout and product pages are hidden behind login portals?"
}

Live queries from incoming AI agents

GET /api/v1/stream/status
STREAMING: ACTIVE
{"status": "listening", "endpoint": "/api/v1/stream/live-queries", "active_feed": true}
GET /api/v1/queries/all
BATCH (14 QUERIES)
{
"total_queries": 14,
"type": "full_queries_catalog",
"data": "[ /* Array of all 14 live AI agent query prompts & intent tags */ ]"
}

Why This Architecture Wins

GET /api/v1/architecture/benefits-title
{
"title": "Why This Architecture Wins"
}

Agent Experience (AX)

Built for the agentic web, moving beyond human-centric browser rendering to provide purpose-built views and optimal data structures for AI systems.

GET /api/v1/architecture/agent-experience
{
"title": "Agent Experience (AX)",
"description": "Built for the agentic web, moving beyond human-centric browser rendering to provide purpose-built views and optimal data structures for AI systems."
}

Instant Freshness & Zero Stale Data

Replaces outdated indexed pages with direct on-site agent responses, ensuring AI models always serve up-to-date pricing and accurate details.

GET /api/v1/architecture/freshness-data
{
"title": "Instant Freshness & Zero Stale Data",
"description": "Replaces outdated indexed pages with direct on-site agent responses, ensuring AI models always serve up-to-date pricing and accurate details."
}

Bandwidth & Server Cost Protection

Eliminates heavy headless browsers and anonymous bot traffic, turning resource-intensive page rendering into lightweight typed API responses that keep your infrastructure fast and stable.

GET /api/v1/architecture/bandwidth-protection
{
"title": "Bandwidth & Server Cost Protection",
"description": "Eliminates heavy headless browsers and anonymous bot traffic, turning resource-intensive page rendering into lightweight typed API responses that keep your infrastructure fast and stable."
}

Reduced Compute Costs for AI Engines

Minimizes token usage and processing overhead for answer engines and LLM crawlers, creating a mutually beneficial and efficient ecosystem.

GET /api/v1/architecture/reduced-compute
{
"title": "Reduced Compute Costs for AI Engines",
"description": "Minimizes token usage and processing overhead for answer engines and LLM crawlers, creating a mutually beneficial and efficient ecosystem."
}

Real-Time Intent Analytics

Tracks live user queries and agent prompts as they happen, surfacing hidden pain points, missing content gaps, and actionable feedback to improve your products.

GET /api/v1/architecture/intent-analytics
{
"title": "Real-Time Intent Analytics",
"description": "Tracks live user queries and agent prompts as they happen, surfacing hidden pain points, missing content gaps, and actionable feedback to improve your products."
}

Proprietary Data Ownership for Custom AI Models

Extracts your site's absolute interaction data and live conversational telemetry, giving you a proprietary asset to train custom AI models, such as pipelines built with River.ai, that are fully owned and operated by your business.

GET /api/v1/architecture/data-ownership
{
"title": "Proprietary Data Ownership for Custom AI Models",
"description": "Extracts your site's absolute interaction data and live conversational telemetry, giving you a proprietary asset to train custom AI models, such as pipelines built with River.ai, that are fully owned and operated by your business."
}

We believe companies that successfully manage and monetize their agent traffic will define the next decade.
Embassia is built for that.

GET /api/v1/manifesto/vision
{
"statement": "We believe companies that successfully manage and monetize their agent traffic will define the next decade. Embassia is built for that."
}
ANSWERS

FAQ

How on-site agents work and why it's better than anything else?

GET /api/v1/faq/metadata
{
"section": "ANSWERS",
"title": "FAQ",
"description": "How on-site agents work and why it's better than anything else?"
}
01

How is LLM Search Console different from traditional AEO or SEO tools?

Traditional AEO platforms rely on third-party consumer panels, historical approximations, and statistical modeling to guess how users interact with AI. They show you simulated trends after the fact. Embassia bypasses estimates entirely by deploying an on-site agent that captures live, real-time prompts and intent signals directly at the moment the AI crawler visits your actual website.

GET /api/v1/faq/q01-difference
{
"id": "01",
"question": "How is LLM Search Console different from traditional AEO or SEO tools?",
"answer": "Traditional AEO platforms rely on third-party consumer panels, historical approximations, and statistical modeling to guess how users interact with AI. They show you simulated trends after the fact. Embassia bypasses estimates entirely by deploying an on-site agent that captures live, real-time prompts and intent signals directly at the moment the AI crawler visits your actual website."
}
02

Why do AI crawlers and bots prefer using our endpoints instead of traditional scraping?

Traditional scraping forces AI models and tools to drive heavy headless browsers. They boot instances, render JavaScript, and waste massive server resources. By communicating directly with your on-site agent through lightweight typed endpoints, AI crawlers get accurate data instantly, saving compute overhead, eliminating hallucinations, and bypassing bot blocks entirely.

GET /api/v1/faq/q02-endpoints
{
"id": "02",
"question": "Why do AI crawlers and bots prefer using our endpoints instead of traditional scraping?",
"answer": "Traditional scraping forces AI models and tools to drive heavy headless browsers. They boot instances, render JavaScript, and waste massive server resources. By communicating directly with your on-site agent through lightweight typed endpoints, AI crawlers get accurate data instantly, saving compute overhead, eliminating hallucinations, and bypassing bot blocks entirely."
}
03

How does Embassia protect my servers from bot traffic and heavy scrapers?

By turning resource-intensive browser rendering and anonymous scraping into lightweight, typed API responses. This slashes backend compute costs, eliminates wasted bandwidth, and keeps your infrastructure stable even as AI traffic surges.

GET /api/v1/faq/q03-protection
{
"id": "03",
"question": "How does Embassia protect my servers from bot traffic and heavy scrapers?",
"answer": "By turning resource-intensive browser rendering and anonymous scraping into lightweight, typed API responses. This slashes backend compute costs, eliminates wasted bandwidth, and keeps your infrastructure stable even as AI traffic surges."
}
04

Which APIs or models does the on-site agent use to communicate?

It dynamically matches the visitor. Whether it is ChatGPT, Claude, Gemini, Perplexity, Copilot, Meta AI, or Grok, the on-site agent detects the incoming crawler and responds using that exact model's native API. Whichever foundational model is querying your site, your agent speaks its exact protocol to deliver clean, typed data instantly.

GET /api/v1/faq/q04-protocols
{
"id": "04",
"question": "Which APIs or models does the on-site agent use to communicate?",
"answer": "It dynamically matches the visitor. Whether it is ChatGPT, Claude, Gemini, Perplexity, Copilot, Meta AI, or Grok, the on-site agent detects the incoming crawler and responds using that exact model's native API. Whichever foundational model is querying your site, your agent speaks its exact protocol to deliver clean, typed data instantly."
}
05

What kind of insights do I get in the LLM Search Console?

You get real-time visibility into high-intent customer prompts, exact friction points, missing content gaps, and conversational telemetry extracted straight from foundational model crawlers (like ChatGPT, Claude, and Gemini).

GET /api/v1/faq/q05-insights
{
"id": "05",
"question": "What kind of insights do I get in the LLM Search Console?",
"answer": "You get real-time visibility into high-intent customer prompts, exact friction points, missing content gaps, and conversational telemetry extracted straight from foundational model crawlers (like ChatGPT, Claude, and Gemini)."
}
06

Do I need to change my existing website architecture?

No. You simply convert your website pages into clean, typed endpoints, deploy your on-site agent, and let the system automatically manage incoming AI traffic without disrupting your human-facing frontend.

GET /api/v1/faq/q06-architecture
{
"id": "06",
"question": "Do I need to change my existing website architecture?",
"answer": "No. You simply convert your website pages into clean, typed endpoints, deploy your on-site agent, and let the system automatically manage incoming AI traffic without disrupting your human-facing frontend."
}

The Agentic Layer for the Web

GET /api/v1/footer/tagline
{
"tagline": "The Agentic Layer for the Web"
}