Enables semantic search across indexed documents using vector embeddings. Index GitHub repositories and URLs to perform natural language queries with AI-enhanced contextual results.
Enables AI agents to search and retrieve context from GitHub issues, pull requests, releases, and documentation using hybrid semantic search and time-ordered activity scans.
Enables AI agents and IDEs to ingest and search code repositories using hybrid retrieval (dense + sparse) with exact line-level citations for precise code analysis.
Enables AI coding assistants to search and retrieve information from a locally ingested knowledge base using hybrid search, grounded in user-curated documentation.
Provides semantic code search and retrieval capabilities for AI agents, enabling them to query codebases using natural language with automatic learning, hybrid search, and intelligent chunking of functions and classes.