Summary
A search engine built for AI — embeddings-based retrieval that finds pages by meaning, not keyword overlap.
Description
Exa is a web search API designed for agents rather than people. Its index is built on embeddings, so a query can describe the kind of page you want — "startups building developer tools for observability, founded after 2023" — and get results that match the description rather than the wording.
What it offers
- Neural search over a large web index, returning results by semantic match
- Full page contents with each result, so an agent does not need a separate fetch-and-parse step
- Highlights and summaries extracted per result for the specific query
- Similarity search. Give it a URL and get pages like it, which is remarkably effective for competitor and prospect discovery.
- Filters by domain, date, and content type
- Research and Answer endpoints that run multi-step retrieval and return a cited answer or a structured report
- Websets for building curated collections of entities matching a description
Where it fits
Deep research agents, market and competitor mapping, recruiting and prospecting, and any RAG system where the web is the corpus. Free credits to start, usage-based pricing per search, with SDKs for Python and TypeScript and MCP support.
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