Glossary term
Semantic Search
Search that matches by meaning and intent, not only by exact keywords.
What it is
Semantic search is search by meaning, which lets users find relevant content even when the query and the document use different words for the same idea.
Key Takeaways
- Semantic search improves discovery when terminology varies across documents.
- It is a core building block for useful document question answering.
- Buyers should compare whether a vendor combines semantic retrieval with evidence-rich review.
Why it matters
Semantic search helps users find relevant passages even when the wording in the question does not exactly match the wording in the document. That matters in enterprise environments where the same idea may be expressed differently across policies, contracts, reports, or forms. For buyers, semantic search matters because it determines whether the platform helps people discover the right evidence quickly or forces them to guess the right terminology before they can get value.
How OdysseyGPT uses it
OdysseyGPT combines semantic search with citation-backed review. Users can ask natural questions instead of constructing keyword logic, and the platform returns the passages most likely to answer the question. That same retrieval layer supports question answering, cross-document analysis, and issue spotting across large document collections.
Evaluation questions
Why does semantic search matter in document review?
Because reviewers often know the issue they are looking for but not the exact words a counterparty, regulator, or author used to express it.
Is semantic search enough on its own?
No. It is most useful when combined with citations, cross-document analysis, and a workflow that lets reviewers validate what was retrieved.
How does OdysseyGPT use semantic search?
OdysseyGPT uses semantic search as the retrieval layer behind question answering, issue spotting, and evidence-backed document review.