Give the assistant relevant source material
Retrieval-augmented generation, often shortened to RAG, retrieves information and supplies it as context for a generated answer. In a business assistant, that material might be approved product guides or internal procedures. It is a way to connect answers with reference information, not a guarantee that every answer will be correct.
Clean the knowledge collection
Start with a small set of current documents. Remove duplicates, mark superseded versions and assign an owner to each policy. If the collection contains conflicting procedures, the assistant may retrieve the wrong one or combine incompatible information. Better retrieval cannot resolve an ownership decision the business has never made.
Enforce permissions before retrieval
A user should only retrieve material they are allowed to access. Do not fetch everything and ask the model to keep confidential sections secret. Apply access controls in the retrieval system and test them with users from different roles or companies. A natural-language instruction is not a substitute for authorization.
Make answers inspectable
Show references to the relevant source passages and allow the assistant to say that the supplied material is insufficient. For a product support example, test questions about discontinued items and missing specifications. The answer should not fill a gap with a plausible-sounding value. Keep a direct route to human support.
Evaluate both retrieval and answers
When an answer is wrong, check whether the right document was retrieved and whether the model used it correctly. Track these as different problems. Refresh the collection through a controlled process and repeat tests after updates. Begin with a narrow topic where the team can verify answers before expanding the knowledge base.
Published by DevMania with AI assistance. Examples illustrate planning approaches and do not claim client results. Check current provider documentation before implementing product-specific features.