Hybrid Search
Definition
Hybrid search combines different search signals, typically full-text/keyword search and vector search.
Lexical methods find exact terms, while semantic vector search finds similar meanings. A ranking or fusion method combines both result lists.
Simply explained
How to simultaneously search for exactly matching words and for semantically similar formulations.
Why it matters in practice
Highly relevant for RAG and enterprise search because technical terms, article numbers, and semantic questions require different search signals.
Example from business
A spare parts assistant combines BM25 for exact part numbers with embedding search for naturally formulated error descriptions.
Limits and pitfalls
- Uncritically adding scores from different methods; failing to effectively enforce permissions before sharing with users or language models; overlooking recall losses due to filter mode; not validating weighting against real search queries.
Origin & history
Hybrid search combines established information retrieval methods with modern vector search. Current search platforms support various fusion and reranking methods.
Use in mid-sized companies
- Possible applications: enterprise search, RAG, support knowledge, product and document research.
Frequently asked questions
Is Hybrid Search automatically better?
No, it must be evaluated against real search queries. Why not only vector search? Exact terms and IDs often benefit from lexical search.
Sources
- Hybrid Search · Microsoft Azure AI Search, Hybrid Search
- Filters in vector queries · Microsoft, Filters in vector queries
Source verification: 10./11.10.2026.
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