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Pricing is based on the duration and terms of your contract with the vendor, and additional usage. You pay upfront or in installments according to your contract terms with the vendor. This entitles you to a specified quantity of use for the contract duration. Usage-based pricing is in effect for overages or additional usage not covered in the contract. These charges are applied on top of the contract price. If you choose not to renew or replace your contract before the contract end date, access to your entitlements will expire.
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The Exa.ai Web Search API delivers fast, high-quality, and semantically enriched web search results for developers, researchers, and enterprises. It supports both neural (semantic) and keyword-based queries, along with features like full content extraction, highlights, summaries, and direct answers.
Lock in an Enterprise contract to get volume discounts, higher QPS, 1-1 support, custom MSA, custom data categories and more.
This listing bills through a contract. You commit to the Exa Base Enterprise Plan, which sets your baseline usage for the web search API. It bundles volume discounts, higher query rates, custom terms, and direct support. The additional_usage dimension covers consumption beyond your committed baseline. It bills per unit as you exceed the plan's included amount. Together, these two dimensions form a commitment-plus-overage model: your enterprise contract defines the base, and extra usage scales your cost when demand rises above it.
Top-of-mind questions for buyers
What counts as one unit for the web search API billing?
A unit maps to API requests against the search index. Basic search calls, full page content retrieval, and research runs each consume units at their own rates. Content extraction meters per page, while search endpoints meter per request. Contact enrichment for emails and phone numbers bills separately from search usage.
What happens when my usage passes the amount included in my enterprise plan?
Your committed Exa Base Enterprise Plan sets an included baseline. Once your requests exceed that baseline, the additional_usage dimension meters the overflow per unit. This overage applies only to consumption above the included amount, not to your whole volume. Charges scale as demand rises above your committed level.
Which activity drives most of the cost — searches or content retrieval?
Both bill at the same time on one invoice. Search request volume tends to dominate for agents making frequent queries. Full page content retrieval and research runs add cost when you pull large amounts of page text or run deep, multi-step tasks. Contact enrichment bills separately when used.
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High-Signal Neural Search with Snappy Performance and Easy Onboarding
Reviewed on Jun 10, 2026
Review provided by G2
What do you like best about the product?
The quality of the search results is easily the standout feature. When you’re feeding data into LLMs, the output is only as good as the retrieval step, and Exa’s neural search consistently surfaces high-signal content that traditional APIs tend to miss. On top of that, performance feels incredibly snappy, and the API documentation made onboarding straightforward. Overall, it’s a major upgrade for any AI-driven search workflow.
What do you dislike about the product?
When you’re building autonomous agents that run in continuous loops, rate limits and API costs can quickly become a bottleneck as you scale. It’s fantastic for prototyping, but once you deploy agents that need constant, high-volume context retrieval, you have to pay close attention to optimization to keep usage costs under control.
What problems is the product solving and how is that benefiting you?
We struggled to feed high-quality, highly relevant context into our autonomous coding agents. When we were building reinforcement learning environments or SWE-agents, traditional search APIs produced too much noise and often returned poorly formatted HTML. Exa addresses this by offering semantic, neural search that delivers clean, structured data directly to our LLMs. The result is noticeably better agent accuracy, along with hours saved because we no longer have to build and maintain custom web scrapers.