RAG – Retrieval Augmented Generation
RAG explained: How AI responses are backed up by your company's own documents and why this reduces hallucinations.
IT Glossary
In brief
Retrieval Augmented Generation (RAG) combines a language model with a search across your own documents. Instead of answering solely from its training knowledge, the system first searches for relevant passages in manuals, policies, contracts or wikis and formulates the response on this basis, complete with source citations.
The practical benefit: Responses become verifiable, remain up to date with the stored documents and can be restricted to a defined body of knowledge. This significantly reduces fabricated information, but does not replace expert verification.
Technically, this includes document processing, vector search and permissions checking: an employee is only permitted to see via the AI what they would also be allowed to see directly. It is precisely this permissions question that is clarified by the Copilot Readiness Assessment.
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