Enables agents to perform semantic search, text comparison, clustering, and zero-shot classification locally without API costs, allowing repeated in-loop use.
Enables local document semantic search and retrieval for DeepSeek Harness agents, with source citations and fully local embedding without external APIs.
Provides a local vector memory store for AI agents with semantic search, offline embeddings, and MCP integration, enabling tools like Claude and Cursor to store and retrieve information without cloud dependencies.
Enables AI agents to index and search local files, websites, GitHub repos, and packages with hybrid AI-powered retrieval, all locally through IDE chat.
Enables AI agents to maintain persistent, local memory with retrieval-augmented search, knowledge graphs, and context surfacing, without any cloud dependencies.