Semantic search uses embeddings to match a query to documents based on conceptual similarity rather than keyword overlap. A user searching for "supplier payment delay" will surface documents about "vendor invoice overdue" or "accounts payable backlog" — even if those exact words do not appear in the query.
In enterprise knowledge environments where users do not always know the exact terminology used in documents — and where different teams often use different words for the same concepts — semantic search dramatically improves recall. It is the difference between finding what you are looking for and only finding it when you happen to use the right words.
