Semantic Search
Search that matches by meaning rather than exact keywords, using vector similarity over embeddings.
What is Semantic Search?
Semantic search finds relevant content even when the query uses different words than the source document. It is the retrieval engine behind RAG and the reason AI assistants can answer questions about internal knowledge bases without exact keyword matches. See Semantic Search.
Why it matters for on-premise & regulated AI
Semantic search over internal knowledge — Jira, Confluence, SharePoint, code repositories — is usually the first AI capability an enterprise deploys, and the first place permissions break. Running it on-premises keeps the embedding index inside your boundary and lets retrieval respect the source system’s access controls per user, so search results never become a side channel around document permissions.
Read the full guide: Semantic Search — in-depth article →
Related terms
Putting Semantic Search to work?
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