Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.

Context engineering for AI agents. ~80% fewer tokens. Fix tool overload. Skills and memory with in-process BM25 and semantic retrieval. Progressive Disclosure. No vector DB.

A lightweight, lightning-fast, in-process vector database

A bio-inspired cognitive memory engine — a new paradigm for Graph RAG.

Turn scattered knowledge, operational data, and history into source-linked context that your agents can inspect, explain, and reuse.