Query optimization involves refining a query before it is processed so that the AI retrieves more precise and contextually relevant results. This might include rephrasing an ambiguous query, decomposing a complex question into sub-queries, adding relevant context, or removing noise.
Good query optimization significantly improves retrieval quality in RAG systems and enterprise search without requiring changes to the underlying models or indexes. It is one of those high-leverage improvements that operates entirely at the input layer — cleaning up the question so the retrieval system has the best possible signal to work with.
