Skip to main content
Core concept · AI Search Infrastructure

Definition

Hybrid retrieval combines two ways of finding content, lexical matching on exact terms and semantic matching on meaning, and merges their results. It pairs a keyword method like BM25 with a dense, embedding-based method, so both precise term matches and conceptual matches surface. It is now the default in serious AI search systems. Neither keyword nor semantic search catches everything on its own. Lexical methods nail exact terms and proper names but miss paraphrase. Semantic methods catch meaning but can drift on specifics. Hybrid retrieval recovers both, which is why it has become standard. For content, it means a page needs the exact terms a buyer might type and the surrounding meaning a model reasons over. Writing for one path and ignoring the other leaves half of retrieval closed.

Dense retrieval

See also

Sparse retrieval

See also

Semantic search

See also

Keyword search

See also

Reranking

See also

Relevant Plate Lunch Collective Services

AI SEO Citation-Ready Content