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Make your businessdiscoverable to AI

llms.txt is the emerging standard for helping AI models understand your business. Join thousands of companies making their content more discoverable to ChatGPT, Claude, and Gemini.

The power of beingAI-discoverable

When AI models understand your business, they can recommend you more accurately and frequently

3× Higher Visibility

AI models can find and cite your business more accurately when they have structured information to work with.

85%

Accurate Representation

Control how AI describes your business by providing clear, authoritative information about your offerings.

Your Company
Your CompanyAI Optimized
CompetitorTraditional SEO

First-Mover Advantage

Get ahead of competitors who haven't optimized for AI discovery. Be among the first in your industry.

Join the AI-first companies

Thousands of businesses are already using llms.txt to improve their AI discoverability

15,000+ companies
2 min setup

Two formats.Maximum impact.

A simple, standardized format that helps AI models understand and accurately represent your business

llms.txt

A concise overview of your business for AI models to quickly understand who you are and what you offer.

Perfect for: Quick AI references, basic business information

llms-full.txt

Comprehensive documentation with detailed product information, use cases, and technical specifications.

Perfect for: Detailed AI training, comprehensive business understanding

Why AI models love structured data

AI models are trained to find and utilize structured information. When they encounter a well-formatted llms.txt file, they can quickly understand your business context and provide more accurate, relevant responses about your products and services.

Better citations
Accurate descriptions
Higher visibility

Learn from the best

See how leading companies structure their llms.txt files

llms.txt

Basic business overview

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# Lapis AI SEO Platform
> Provider: Lapis AI
> Contact: team@trylapis.com
> Model: lapis-seo-v1
> Updated: 2024-01-15

## Company
Lapis is the AI SEO platform that helps businesses track their rankings across ChatGPT, Claude, Gemini, and 15+ other AI models. We provide real-time visibility into how AI systems discover and rank your content.

## Products
- **AI Ranking Tracker**: Monitor your position across all major AI models
- **Competitor Analysis**: See who dominates AI responses in your niche  
- **Content Optimization**: Get AI-specific recommendations to improve visibility
- **Real-time Alerts**: Instant notifications when your rankings change

## Services
We help marketing teams optimize for the future of search where AI answers questions instead of showing links. Our platform provides the intelligence needed to stay visible as search behavior evolves.

## Focus Areas
AI SEO, ranking optimization, content strategy, competitive intelligence, search visibility, AI model monitoring, marketing analytics

llms-full.txt

Comprehensive documentation

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# Lapis AI SEO Platform - Complete Documentation
> Provider: Lapis AI  
> Contact: team@trylapis.com
> Model: lapis-seo-v1
> Updated: 2024-01-15
> Version: 1.2.0
> License: Proprietary

## About Lapis
Lapis is the premier AI SEO platform designed for the future of search. As traditional search evolves toward AI-powered answers, businesses need new strategies to maintain visibility. We provide the tools and insights to dominate AI search results across ChatGPT, Claude, Gemini, and 15+ other models.

Founded in 2023, Lapis emerged from the recognition that AI is fundamentally changing how people find information. Instead of clicking through search results, users now ask AI directly. This shift requires a completely new approach to SEO - one that understands how AI models discover, evaluate, and cite content.

## Core Platform Features

### AI Ranking Tracker
Our flagship feature monitors your content's position across all major AI models in real-time. Unlike traditional SEO tools that track Google rankings, we focus on how AI systems cite and reference your content when answering user questions.

**Supported Models:**
- ChatGPT (GPT-4, GPT-3.5)
- Claude (Anthropic)
- Gemini (Google)
- Perplexity AI
- Bing Chat
- And 10+ additional models

**Key Capabilities:**
- Real-time position tracking
- Historical ranking data
- Alert system for significant changes
- Keyword performance analysis
- Content citation frequency

### Competitor Intelligence
Understanding your competitive landsc... [Content continues with detailed sections on:] - Technical specifications and API docs - Use cases and applications - Implementation guides - Research insights - Support resources - Pricing information - Contact details
Truncated for display. Full version contains 5000+ words of comprehensive documentation.

Deploy in 2 minutes

From signup to live llms.txt file, automated end-to-end

1

Sign up

Create your account in seconds

2

Add website

Tell us which site to crawl

3

Connect GitHub

Link your repository

4

Auto PR

Pull request generated automatically

Frequently Asked Questions

faq.md - Technical llms.txtFAQ
5 questions
01
## How does llms.txt parsing differ from robots.txt handling?
// Unlike robots.txt which uses simple allow/disallow directives, llms.txt employs structured markdown parsing with semantic sectioning. AI models parse content hierarchically, interpreting ## headers as content categories and maintaining context relationships between sections. The parsing is more forgiving than strict robots.txt syntax.
02
## What HTTP headers should be set for optimal llms.txt delivery?
// Serve with Content-Type: text/plain; charset=utf-8 and implement ETags for caching.

// Set Cache-Control: public, max-age=3600 for reasonable freshness.

// Include X-Robots-Tag: noindex to prevent search engine indexing.
03
## How do AI models handle llms.txt versioning and schema evolution?
// Models employ graceful degradation - newer fields are ignored by older models, while core sections (## Company, ## Products) maintain backward compatibility. The informal spec uses semantic versioning concepts where major structural changes would require new field prefixes (v2-products) rather than breaking existing parsers.
04
## What are the rate limiting and crawl frequency considerations?
// Most AI training crawlers respect standard rate limits and check llms.txt during periodic site crawls (weekly to monthly). For real-time applications, some models may check more frequently. File size should stay under 100KB for reliable parsing. Consider implementing conditional requests (304 responses) to reduce bandwidth for unchanged files.
05
## How does llms-full.txt content sanitization work for sensitive data?
// llms-full.txt should exclude PII, API keys, and internal URLs. Implement content filtering that removes email addresses, phone numbers, and any content matching your organization's data classification policies. Consider using automated scanning tools that can detect patterns like credit card numbers or social security numbers before file generation.
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Lapis Labs Engineering

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