A neural search engine and API designed for AI applications, using embeddings-based search to find semantically relevant web content rather than simple keyword matching.
Features
Neural, embeddings-based semantic search
Search API built for AI applications
Content and full-text retrieval
Similarity search for finding related content
Filters for date, domain, and content type
Fast API response times
Free tier for developers to test
Integration support for AI agent frameworks
Pros and Cons
Pros
Semantic search finds conceptually relevant results even without exact keyword matches
Well suited to research-style queries where meaning matters more than exact phrasing
Built specifically with AI application developers in mind
Similarity search feature is useful for finding related content at scale
Cons
Semantic search can occasionally surface less relevant results than a precise keyword search would for narrow queries
Another API dependency and cost on top of your core AI model spend
Coverage and freshness depend on Exa's own web index rather than a dominant general search engine