Medical RAG for FDA and WHO QA

video1.0<iframe src="https://www.loom.com/embed/d06f324022714527a00d1ff94a460e68" frameborder="0" width="1796" height="1347" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>13471796Loomhttps://www.loom.com13471796https://cdn.loom.com/sessions/thumbnails/d06f324022714527a00d1ff94a460e68-0ce6c8fa8ba88693.gif529.387Medical RAG for FDA and WHO QAThis Loom presents the Medical RAG project, a retrieval augmented generation system for answering questions about regulatory and responsible AI based on FDA and World Health Organization documentation. The presenter emphasizes that it is not a medical diagnosis or treatment tool, but a domain Q and A system, with ingestion, chunking with metadata, embedding via AWS Titan, and storage in a pgvector database. At query time, questions are embedded, similar documents are retrieved, and reasoning is handled using AWS Bedrock with an OPPOS 4.6 model, exposed through a FastAPI and MCP server with a simple UI. The demo shows example questions, estimated response time, and answers with citations and source references.