Search architecture guide

Semantic search vs. vector search: what each term really means

Semantic search is the goal of matching meaning. Vector search is one method for reaching that goal. Production systems often combine vectors, keywords, filters, and reranking.

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Permission-aware

Measured before launch

01

Semantic search describes behavior

Semantic search attempts to retrieve information based on concepts and intent rather than exact shared words. A user can ask about resetting credentials and find a document titled account access recovery even when the wording differs.

Vectors are a common implementation. An embedding model converts queries and content into numeric representations; a vector index finds nearby representations. The usefulness of those neighbors depends on the model, content preparation, domain language, filters, and ranking strategy.

02

Why keyword search still matters

Exact terms carry critical meaning in business information: product codes, statute numbers, customer names, error messages, acronyms, versions, and quoted phrases. Pure vector retrieval can miss these signals or return conceptually similar but inapplicable content. Keyword systems also provide mature filtering, highlighting, and ranking controls.

03

Hybrid search combines evidence

✓

Keyword retrieval preserves exact language and rare identifiers

✓

Vector retrieval finds conceptual and paraphrased matches

✓

Metadata filters enforce scope, permissions, dates, types, and versions

✓

Rank fusion combines candidate lists

✓

Rerankers compare the query with candidate passages more precisely

✓

Business rules promote authoritative or applicable sources

04

Choose with a representative query set

Build evaluation questions across exact identifiers, broad concepts, ambiguous language, restricted content, recent updates, and missing answers. Compare recall, ranking, latency, cost, and operational complexity. The winning approach is frequently hybrid, but the weighting and components should be justified by evidence.

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Questions

Frequently asked questions

No. Semantic search is meaning-oriented retrieval. Vector search is a technical method often used to implement it.

Hybrid search combines multiple retrieval signals, commonly keyword and vector results, and may add filters, business rules, and reranking.

It depends on the corpus and questions. Evaluate keyword, vector, and hybrid approaches against representative queries and expected evidence.

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