Technology subcategory
RAG
Retrieval-augmented generation — grounding answers in documents and indexes.
RAG technologies ingest, chunk, index, and retrieve context so models answer from *your* corpus instead of parametric memory alone.
They sit between document intake (including DM vendors) and agent frameworks. Quality fails when chunking, ranking, or freshness are invisible — treat RAG as a measured pipeline, not a checkbox.
See also Vector DBs, Search & Web Access, and Memory.
See also
Technologies
Features
Stacks
Document management
GitHub in this term
Primary repositories linked from member packs and devices.