Hybrid Retrieval
The standard AI retrieval architecture combining keyword search and semantic search simultaneously for better coverage.
Plain Language Definition
Hybrid retrieval means running a traditional keyword search and an AI semantic search at the same time, then combining the results. This approach captures both exact keyword matches and conceptually related content, giving AI answer engines more complete coverage. Most production AI search systems use hybrid retrieval because neither keyword-only nor semantic-only retrieval performs as well in isolation.
Technical Definition
Parallel execution of sparse lexical retrieval (BM25 or similar) and dense vector retrieval passes, followed by a fusion operation (typically RRF) to produce a merged candidate set that leverages the complementary strengths of both retrieval modalities.
Why This Matters for AI Search Visibility
Hybrid retrieval is why content needs to satisfy both precision and coverage — using the right terminology for lexical matching while being semantically coherent for vector retrieval. Content that excels at only one dimension performs worse in hybrid systems than content that does both.