What Is Semantic Search? Finding Results by Meaning, Not Just Keywords
Traditional search matches literal words. Semantic search matches meaning — finding relevant results even when the query uses completely different wording.
Matching meaning instead of exact words
Semantic search finds results based on meaning rather than exact keyword overlap, so a query like "affordable laptop" can still surface a result about a "budget notebook" even though they share no words in common. It works by comparing embeddings — numeric representations of meaning — rather than matching literal text.
How it actually works
Both the search query and the content being searched get converted into embeddings, and a vector database finds the stored content whose embeddings are mathematically closest to the query's — closeness in that numeric space stands in for closeness in meaning.
Where keyword search still wins
Semantic search isn't strictly better in every case — exact keyword matching remains more reliable for precise lookups like a product code, an exact phrase, or a specific name, which is why many real systems combine both approaches via hybrid search rather than relying on semantic search alone.
Frequently Asked Questions
What is semantic search?
A search approach that finds results based on meaning rather than exact keyword matching, using embeddings to compare the meaning of a query against stored content.
Is semantic search always better than keyword search?
No — keyword search remains more reliable for precise lookups like exact phrases, codes, or names. Many systems combine both through hybrid search rather than relying on semantic search alone.