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Exa

Search engine and API from San Francisco built for AI agents, with neural web search, page contents, deep research, and people search.

7.7/10
Overall Score
Recommend

Exa runs its own index and ranks pages by meaning, which gives coding agents and research tools better results from one query than keyword search APIs.

Best for

AI product teams building agents, coding assistants, and research tools that need high-quality web results and page text from a single API.

Not ideal for

Teams that only need Google-style results for SEO tracking, or buyers who want one flat monthly price.

Verdict

Exa is a search company in San Francisco, started in 2021 by Will Bryk and Jeff Wang, who met as freshmen at Harvard. AI companies such as Cognition, CodeRabbit, and HubSpot use its API to search the web, pull clean page contents, run multi-step deep research, and find people and companies. It stands out because Exa crawls and indexes the web itself and trains its models to predict useful links, so an agent can ask in plain language and get pages that match the meaning rather than the keywords.

Score Breakdown

How Exa scores in the categories that matter to its buyers.

Buyer outcomes

Result quality for agents
8.5
Speed & one-call coverage
8.0
Breadth of endpoints
7.9
Cost predictability
6.8

Company & commercial

Innovation & product leadership
7.8
Project management & communication
7.6
Pricing
7.4
Contract fairness
7.5

Pricing

Exa publishes usage prices per thousand requests. A free tier comes with monthly credits and no payment method.

PlanPriceWhat stands out
Starter$0$10 of credits every month plus a $10 onboarding bonus
SearchFrom $4 / 1,000 requestsWeb search tool calls for agents
Contents$1 / 1,000 pagesClean page text for results
Deep Search$12–15 / 1,000 requestsMulti-step agent workflows
EnterpriseCustomVolume pricing, custom data providers, enterprise controls

The Field at a Glance

How Exa compares with other AI web search APIs vendors we reviewed, by Overall Score and relative typical engagement cost.

6 7 8 9 Overall Score $ $$ $$$ $$$$ Relative typical engagement cost Linkup Valyu Exa 7.7
Exa Linkup Valyu

Exa scores 7.7 in AI web search APIs, ahead of Linkup (7.5) and Valyu (7.2). Relative cost lands mid-band for this subcategory.

Use-case matrix

Use caseFitNotes
Coding agents and assistantsStrongCognition says Exa powers all parts of Devin.
Research and deep searchStrongDeep Search runs multi-step queries for agents.
People and company searchStrongExa indexes more than a billion people profiles.
Code review contextStrongCodeRabbit reports one Exa search replacing several from its old provider.
SEO rank trackingWeakExa does not mirror Google's result pages.
Fixed monthly budgetsMixedUsage pricing varies by endpoint and depth.

Who it’s for

Good fit

  • AI agent companies
  • Developer tools that need web context
  • Sales and research tools enriching records

Poor fit

  • SEO teams tracking Google rankings
  • Buyers who want one flat price
  • Teams with no engineers

Review Excerpts

Below are excerpts from public reviews. Our team scoured public reviews, forums, and chat rooms to get a balanced view of customers' experience with this company. Paid reviews and pay-for-play sites such as Clutch were excluded.

How it's used

“Traditional search engine solutions weren't enough for us. Exa powers all parts of Devin.”

Walden Yan, Co-founder, Cognition · source
What people like

“Exa consistently shows higher quality than other AI search providers we tested. What Exa is able to do in 1 search took our old provider multiple searches, taking 5 times as long.”

David Loker, VP of AI, CodeRabbit · source
What people like

“We evaluated five different search providers, but none came close to Exa's quality and breadth of data.”

Arda Bulut, CTO and Co-founder, HockeyStack · source
What people don't like

“Deep Search costs $12 to $15 per thousand requests, against $4 for regular search, and our agent wanted to use it for everything. We had to set rules for which steps were allowed to use the deep version.”

ML engineer · r/LangChain

Methodology

This page is an independent evaluation of Exa for buyers comparing options in ai web search apis. AI Industry Reviews accepts no sponsorships, advertising, or pay-for-placement fees. Exa did not pay for this review.

What we scored

The headline number is an Overall Score on a 0-10 scale. Eight criteria sit under it in two groups.

  • Buyer outcomes (for ai web search apis)
    • Result quality for agents
    • Speed & one-call coverage
    • Breadth of endpoints
    • Cost predictability
  • Company & commercial
    • Innovation & product leadership
    • Project management & communication
    • Pricing
    • Contract fairness

Pricing measures whether the price looks fair for the value delivered, including packaging and renewal friction that show up in real buying cycles.

Score Composition

InputWeightWhat it covers
Reviews40%A proprietary read of what practitioners say about likes, complaints, and day-to-day use, including public review sites, forums, and private chat rooms. Paid reviews and pay-for-play sites such as Clutch are out of scope.
Product35%Hands-on look at screens and workflows.
Pricing15%Whether the price looks fair for what you get.
Docs & training10%Docs, tutorials, and training material.

How we balanced the evidence

The Overall Score is the simple average of the eight criteria. Recommendation language follows that score and the fit pattern described above.

Scope

Exa is graded here as ai web search apis. Criteria scores can move as more review volume and product checks are added.

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