What Is Semantic Search?
Semantic search retrieves by meaning rather than by matching words. Both the query and the documents are turned into embeddings, and the system returns the documents whose vectors sit closest to the query’s — so "how do I reset my password" finds a doc titled "account recovery steps" that shares no keywords. It is the retrieval half of modern question-answering, and the reason an agent can find a relevant passage it could never have located by exact-match search.
Where it wins and where it does not
Keyword (lexical) search excels at exact terms — a part number, a name, a rare token — and fails when the query and the answer use different words for the same thing. Semantic search is the inverse: strong on paraphrase and intent, weaker on exact identifiers it was never trained to distinguish. The dense-retrieval line of work established that learned embeddings beat classic lexical scoring on open-domain question answering.
Because each is strong where the other is weak, serious systems run hybrid retrieval — combining lexical and semantic scores — rather than treating semantic search as a replacement. Presenting it as strictly superior to keyword search is a common and costly oversimplification.
Related standards
Questions
Does semantic search replace keyword search?
No — they are complementary. Hybrid retrieval combining both usually beats either alone, especially where exact identifiers matter.
Is semantic search the same as RAG?
No — semantic search is the retrieval step; RAG is the full pattern of retrieving and then generating an answer from what was retrieved.
Keep reading
By Michael Gord · published 2026-10-09 · part of the Agentic Encyclopedia. Dates are the day of publication; events are cited at their own dates.