Exa
Exa is an AI-native search API built on embeddings and link prediction rather than classic keyword search. It returns semantically matching results, can deliver the content directly as Markdown and supports category and domain filters.
Exa is a search API for agents that matches meaning rather than keywords. It returns results with full text, filters by categories such as companies, people or news, and offers an MCP server.
Explanation
For agents, search is not a comfort feature but the line between assertion and evidence. Classic search APIs are built for human keywords; Exa takes natural-language descriptions and returns sources that fit substantively — even when no shared keyword appears. Practically important is the option to include full text right away: the agent saves a second fetch and works on the actual text rather than a snippet. Category filters help avoid noise, for instance when only news or only company pages count. What remains is due diligence: semantically found sources still need checking for date, provenance and suitability before they feed into a statement. No verifiable statements on EU hosting were found in the official sources.
Marketing Relevance
For marketing research Exa shifts the effort: instead of guessing keywords you describe what you are looking for. For accountable owners it matters most that agents can work with citations — a statement with a link is verifiable, one without is not.
Example
For a specialist article the agent should find solid primary sources. The query describes the topic in one sentence, Exa returns matching sources with full text, and the agent cites with date and URL.
Common Pitfalls
Semantic hits look convincing even when outdated or from a dubious source — without checking date and provenance you get apparently sourced nonsense. And without domain filters content farms easily end up in the results.
Origin & History
The company launched in 2021 as Metaphor Systems and renamed to Exa in 2024. Its approach — search over embeddings rather than keywords — began as a research promise and became a sought-after tool as agents spread. By 2026 it added category filters, a research agent and an official, open-source MCP server.
Further Resources
Marketing Use Cases
Source research as a tool inside an editorial agent.
Market monitoring filtered to news and company pages.
Meeting preparation through research on companies and people.
Cited answers in the website chat for questions outside the knowledge base.
Frequently Asked Questions
What distinguishes Exa from a classic search engine?
Exa compares meanings rather than keywords and is designed for machine retrieval: results arrive structured, optionally with full text, and can be filtered by category.
Does Exa replace your own knowledge base?
No. Internal content belongs in your own knowledge base, where rights, currency and authority are settled. Exa adds knowledge from outside.
How do I avoid unreliable sources?
Through domain filters, category filters and a rule that every source used is reported with date and URL. Without that record quality cannot be checked.
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