Retrieval-augmented generation, or RAG, is the technique of supplying an AI model with relevant documents at the moment of asking, so its answer is grounded in that material rather than in memory alone. It is how an assistant is made to answer from your policies and files instead of generalities.
Why it matters for a UK business
It is how a model stops inventing plausible answers and starts citing your actual documents. For any business whose value lives in its own material, it is the difference between a demo and a tool.
What it looks like in practice
The model is given your documents to answer from, retrieves the relevant passages for each question, and grounds its answer in them. Ask about your returns policy and it quotes your returns policy, not a general idea of one.
What to do about it
Get the documents in order before the technology. A knowledge base built on outdated, contradictory files produces confident, wrong answers with citations. The retrieval only works if what it retrieves is true.
Related terms
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If this is the term that has come up in your business and you want it worked through against your own situation rather than in the abstract, that is a conversation, not a page.
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