Hybrid Retrieval Combines Keyword and Semantic Search to Improve RAG Systems

Vector search, which finds documents based on semantic similarity, struggles with exact-match queries such as error codes, product IDs, and technical terms. Hybrid retrieval addresses this by combining multiple search methods — including keyword matching and semantic similarity — to improve information retrieval accuracy. For instance, a keyword search can directly locate a document containing 'ERR-1042', while semantic search handles conceptually related but differently worded queries. Complex questions, such as diagnosing a payment service failure after a deployment, may require pulling from several document types simultaneously, something a single search method cannot reliably handle. Hybrid retrieval systems tackle this by running multiple retrieval strategies in parallel and merging the results for a more complete answer.