RAG (Retrieval-Augmented Generation)
Retrieving relevant passages and passing them into a generation step so answers are grounded in evidence.
What is RAG (Retrieval-Augmented Generation)?
RAG reduces hallucination and gives users source citations. Quality depends on ingestion, chunking, embeddings, ranking, and freshness — “upload documents and chat” is the demo, not the architecture. See RAG Technology Best Practices.
Why it matters for on-premise & regulated AI
RAG determines what your AI knows — and therefore what it can leak. Enterprises deploying RAG over regulated data need the full pipeline (chunking, embedding, indexing, retrieval) to run on infrastructure they control, with document-level permissions enforced at query time. That is the difference between RAG as a demo and RAG as a system a CISO signs off on.
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Putting RAG (Retrieval-Augmented Generation) to work?
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