Crawls documentation websites and provides semantic search capabilities over the content through vector embeddings, enabling natural language queries of technical documentation.
Enables AI assistants to crawl, index, and retrieve information from technical documentation using semantic search, with optional knowledge graph validation for code hallucination detection.
Enables AI coding agents to search, index, and manage documentation libraries with hybrid retrieval and live web fallback, all self-hosted and offline.
Creates and searches private, local RAG libraries from documentation to ground AI assistants in authoritative sources, reducing hallucinations by providing current, accurate context from your own docs instead of relying on outdated training data.