Kotaemon provides a production-ready web interface for document question-answering powered by Retrieval-Augmented Generation. Unlike simpler RAG demos, it implements multi-user authentication with workspace isolation, letting organizations deploy a shared knowledge base where different teams maintain separate document collections with appropriate access controls. The retrieval pipeline supports multiple strategies including dense vector search, sparse BM25 matching, and hybrid combinations that balance semantic understanding with keyword precision.
The agentic reasoning mode enables complex multi-step queries that require synthesizing information across multiple documents or performing intermediate reasoning before generating final answers. Citation support links every response to specific source passages with page numbers and highlighted excerpts, giving users confidence in the accuracy of generated answers. Document processing handles PDFs with OCR for scanned pages, Microsoft Office formats, and images with text extraction, covering the document types commonly found in enterprise knowledge bases.
Backed by Cinnamon AI, a well-funded Japanese technology company, Kotaemon has grown to over 25,000 GitHub stars with 200,000+ Docker pulls. The Apache 2.0 license allows unrestricted commercial use, and the Docker-based deployment provides a straightforward path to self-hosted operation. Human-in-the-loop feedback mechanisms let users rate answer quality, creating a feedback signal for continuous improvement of retrieval and generation quality over time.
