Definition: Hybrid search combines keyword search, such as BM25, with vector or semantic search and merges the two result lists, so a system finds both exact term matches and passages with similar meaning.
Keyword search excels at exact matches like product codes, names and rare terms, but misses paraphrases. Semantic search over embeddings catches meaning but can miss precise identifiers. Running both covers each method's blind spots.
A common approach is reciprocal rank fusion, which scores each document by its rank in each list. Another is a weighted blend of normalized scores. Many pipelines then pass the top candidates to a reranker for a final ordering.
Hybrid search is a standard upgrade for RAG retrieval, enterprise document search, ecommerce catalogs and support knowledge bases. Elasticsearch, OpenSearch, Postgres with pgvector and several vector databases support it, natively or with some glue code.
Build a labeled set of real queries, measure recall and precision for each method alone and combined, and tune weights per content type.
Ryz RAG engineers design and tune retrieval pipelines on your data, working on your team.
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