What Exa does
Exa provides web and code search, page contents, crawling, answer, and research APIs for agents, retrieval systems, and current-data products.
Exa combines semantic and traditional search with content retrieval aimed at model context. It can discover conceptually related pages, return highlights or full text, locate similar links, search technical repositories, and run deeper research. This is useful when an agent needs more than a list of titles but should not receive an uncontrolled browser session.
Pricing is endpoint-specific: search depth, result count, fetched pages, answers, research, and specialized indexes can use different rates. Exa advertises initial credits and pay-as-you-go access, with enterprise arrangements for volume, datasets, and controls. Estimate the whole tool loop, including repeated searches, content fetches, failed pages, and downstream token use.
Semantic relevance can still amplify low-quality or coordinated sources. Full-page content may include copyrighted material, personal data, malicious instructions, or irrelevant navigation. Enforce domain and date policies, cap fetched text, retain citations, respect use restrictions, and keep content outside the instruction hierarchy. High-impact research needs a person to open and validate the strongest sources.
How Exa works
A client sends a natural-language, keyword, URL, or category-constrained request to Exa. Search returns ranked pages, while content options fetch text, highlights, summaries, metadata, or links; specialized endpoints can answer, crawl, find similar pages, research, or search code. The calling application selects evidence and passes only relevant context to a model. People should inspect provenance, licensing, dates, and claims before relying on output.
How to set up Exa
Write a retrieval policy
Define allowed source types, domains, dates, result diversity, content limits, citations, and when the system must abstain.
Create a server-side integration
Protect the key, separate environments, set cost limits, and expose only a narrow internal search interface to agents.
Benchmark search modes
Compare semantic, keyword, category, code, similarity, and content settings on questions with reviewed gold sources.
Defend against hostile pages
Treat fetched content as data, not instructions; sanitize it, restrict links and downloads, and prevent access to secrets or internal networks.
Monitor evidence quality
Track authoritative-source recall, duplicates, staleness, citation support, latency, endpoint spend, and human corrections.
Exa FAQs
What is Exa used for?
It gives AI applications APIs for searching the web, fetching page content, finding similar pages, and running deeper retrieval workflows.
How is Exa priced?
Rates differ by endpoint, search depth, results, and pages fetched. Check the current rate card and model complete agent loops.
Is Exa a vector database?
No. It is a hosted search and retrieval service; applications may still use a vector database for private data.
Does semantic search guarantee trustworthy results?
No. Relevance and authority are different, so sources, dates, and supporting passages require validation.
Can an agent follow instructions found on a page?
It should not do so by default. Web text is untrusted and must remain subordinate to application policies and human authorization.
Listing reviewed 2026-07-30. Product details and pricing can change; verify important terms on the provider's website.
Related Research AI tools
Related AI guides
Reviews
Tell the community what you made, what worked, and what you wish you knew before starting.