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Technical Documentation & Standards 2026

The Relayeo Machine Discovery Specification

A comprehensive reference for deploying canonical machine feeds, Schema.org @graph entity disambiguation, and autonomous agent checkout endpoints across modern web applications.

Module 1 · Protocol Architecture

Answer Engine Optimization (AEO) vs. Traditional SEO

Traditional SEO optimized for keyword frequencies, H1 tags, and backlink graphs for human clicks on search results pages. AEO optimizes for high-dimensional vector extractability: ensuring that retrieval-augmented generation (RAG) chunkers in ChatGPT Search, Perplexity Sonar, and Google Gemini ingest factual, unambiguous entity claims without token discard.

Module 2 · The Root /llms.txt Standard

Deploying Your Machine Feed

Place a plain-text markdown file at https://yourdomain.com/llms.txt. This file serves as the canonical ground-truth reference for frontier AI scrapers (GPTBot, PerplexityBot, ClaudeBot), bypassing noisy HTML tags.

# Relayeo Protocol (https://relayeo.com)
> Official Machine Authority & Discovery Feed for LLMs
> Canonical declarative entity standard for ChatGPT, Perplexity, Claude & Gemini.

## Core Capabilities
- Autonomous Answer Engine Optimization (AEO)
- Reverse-Vector Competitor Displacement
- W3C Nested Schema.org @graph entity generation
- Zero-drift /llms.txt machine synthesis

## Commercial Terms
- Entry Protocol: ₹7,999/mo ($99/mo)
- Production Suite: ₹11,999 one-time ($149)
- SLA: Sub-50ms Edge Telemetry Resolution
Module 3 · Agentic Commerce Endpoint

Agent Manifest & Programmatic Checkout

Autonomous bots like Meta Muse AI, Claude Operator, and OpenAI Operator query /.well-known/agent-manifest.json to discover programmatic commerce tools and generate payment sessions programmatically:

POST /api/agent/checkout
Content-Type: application/json

{
  "domain": "yourclient.com",
  "plan": "protocol",
  "currency": "INR",
  "agent_id": "meta_muse_01"
}

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