Retrieval-Augmented Generation (RAG)
Concept
Training & Inference
Look it up, then answer — how enterprises ground models in their data.
You're looking at a concept explainer: what this term means in plain English, and the records it ties together.
RAG retrieves relevant documents (via embedding search) and feeds them into the model's context, giving current, citable, private knowledge without retraining. It is the default enterprise AI architecture and the reason vector databases and embedding models became infrastructure categories; long context windows compete with it, agents combine both.
How this connects to the rest of the stack
This record's links at a glance — click a group to jump to it.
Sources
Record reviewed as of 2026-01-15 — see Methodology.