Semantic search
Also known as: vector search
What is Semantic search?
Search that matches on meaning rather than exact words. It turns your query into an embedding and finds the content whose meaning sits closest, so a search for "cut cloud costs" also surfaces a page titled "lowering the monthly server bill". It is why modern search and chatbots find the right answer even when the wording differs.
Why it matters
Searching by meaning fixes the classic weakness of keyword search, which is that it fails whenever the user’s words differ from the document’s. But swinging fully to semantic search brings the opposite problem: it can gloss over the cases where the exact string is the point. Search for a specific part number, error code or surname and a meaning-based system may serve up things that are merely related, while plain keyword matching would have nailed it. The strongest search systems rarely pick a side. They run both and blend the results, using meaning to catch paraphrases and exact matching to respect the times a user typed precisely what they wanted.
In practice
An online store replaces keyword search with a semantic system and complaints rise: shoppers typing an exact model number now get loosely related products instead of the item. The fix is a hybrid setup that matches meaning for descriptive queries and exact terms for codes and names. Search quality is not one dial. It is knowing which query deserves which kind of matching.
