Enables AI assistants to search and retrieve information from your knowledge base using RAG (Retrieval-Augmented Generation) with hybrid search, document indexing, and ChromaDB vector storage.
Enables AI coding assistants to search and retrieve information from a locally ingested knowledge base using hybrid search, grounded in user-curated documentation.
Enables AI assistants to enhance their responses with relevant documentation through a semantic vector search, offering tools for managing and processing documentation efficiently.
Enables AI assistants to semantically search through indexed documentation websites and local code repositories using OpenAI embeddings and ChromaDB vector storage.
Enables AI assistants to search and query PDF documents through a local RAG system with vector embeddings. Provides semantic document search capabilities while keeping all data stored locally without external dependencies.
Enables AI assistants to search through structured databases and unstructured content (documents, videos, files) using natural language queries with semantic understanding.