Hybrid Search

What is Hybrid Search?

Hybrid search is a retrieval strategy that runs vector-database-driven semantic search alongside traditional keyword search (such as BM25) and fuses their results.

The point is to leverage the semantic strength of vector search — finding conceptually similar documents — together with the exactness strength of keyword search — nailing proper nouns, code tokens, or literal phrases.

Why Does It Matter?

Real-world queries often need semantic similarity and exact string match at the same time.

• Questions with varied phrasing like "refund policy": vector search wins
• Precise identifiers like "GPT-4o-mini" or "ERR-1042": keyword search wins

Hybrid search combines both signals to cancel each approach's blind spots, reducing both missed results and noise in one pass.

Operational Tips

Start with fixed vector/keyword weights and then tune them against a query-type evaluation set. This staged approach is the most stable way to iterate on hybrid search quality.