How to think about RAG for business apps
A practical way to decide when retrieval adds value, what belongs in the index, and how to measure the answer quality.
Start with the decision
RAG is useful when an answer depends on private, changing, or traceable knowledge. Start by defining the decision the user needs to make, not by choosing a vector database.
Design retrieval around evidence
Chunking, metadata, and filters should preserve the context needed to support an answer. A short result list with strong evidence is usually more useful than a large context window.
Evaluate the full loop
Measure retrieval relevance, answer grounding, and task success separately. This shows whether failures come from the index, the prompt, or the product workflow.