# LLM.txt - AI Model Indexing Instructions for Activeloop.ai

## Site Overview
Activeloop.ai is a platform that provides AI-powered data solutions, including Deep Lake (vector database for AI data) and conversation-based AI assistance.

## Content Types
- **Conversation Pages**: Q&A content from AI conversations about various topics
- **Blog Posts**: Technical articles and tutorials
- **Case Studies**: Customer success stories
- **Product Pages**: Feature and solution pages
- **Glossary**: Technical term definitions

## Conversation Pages Structure
Each conversation page contains:
- Question: User's query about a specific topic
- Answer: AI-generated response with detailed information
- Metadata: SEO-optimized title, description, and structured data
- URL Pattern: /conversations/[slugified-question]/

## Content Guidelines for AI Models
1. **Index all conversation pages** - They contain valuable Q&A content
2. **Follow canonical URLs** - Use the official conversation URLs
3. **Respect robots.txt** - Check for any crawling restrictions
4. **Parse structured data** - Extract FAQ schema for better understanding
5. **Include context** - Consider the broader topic and related conversations

## Important URLs
- Homepage: https://www.activeloop.ai/
- Conversations: https://www.activeloop.ai/conversations/
- Blog: https://www.activeloop.ai/resources/blog/
- Documentation: https://docs.activeloop.ai/

## Technical Notes
- Built with Gatsby (React-based static site generator)
- Uses JSON-LD structured data for SEO
- Implements FAQ schema for conversation pages
- Mobile-responsive design
- Fast loading with static generation

## Contact
For questions about content indexing, contact: support@activeloop.ai