Web search API for AI agents with embedding-based retrieval and structured outputs.
The strongest neural search API for AI agents in 2026. The Highlights feature is the cost-saving detail most teams underestimate.
Last verified: April 2026
Sweet spot: a developer building an agent or RAG pipeline who has hit the limits of keyword search and wants semantic retrieval that just works. Exa's Highlights endpoint is genuinely undervalued — for high-volume RAG it can cut LLM input cost by an order of magnitude versus shipping full pages into context. Failure modes. Exa is API-only — there is no end-user UI, so this is not the tool to pick if you do not have an engineer to integrate it. Costs can grow non-linearly on multi-hop agent flows; profile your typical task before committing. Websets is powerful but data freshness on the company database varies by sector, so spot-check before relying on it for sales workflows. What to pilot. Take the queries your product actually issues, run them through Exa Search and Contents (with Highlights enabled), measure relevance against your current solution and total token cost end-to-end. If Exa wins on relevance at lower combined cost, the migration is worth the engineering hours; if it ties on relevance at higher cost, stay where you are.
Exa is a developer-first web search API designed from the ground up for AI applications. Where Google indexes pages for keyword queries, Exa indexes pages as embeddings and supports neural / semantic search out of the box — you can ask for "startups working on agentic browsers in 2025" and get a ranked list of pages that match the meaning, not just the keywords. It also supports traditional keyword search if you need it. The product surface is four endpoints: Search (semantic or keyword), Contents (extract clean text, summaries, or highlights from a URL), Answer (a one-shot answer endpoint that does the search-and-synthesise step in one call), and Websets (a structured-data product that turns natural-language queries into curated lists of companies, people, papers, etc, backed by a 70M+ company database). Highlights are a token-efficient feature that returns just the relevant 1–3 sentences from a page, which can cut LLM input cost dramatically on RAG flows. Customers include Cursor, AWS, Databricks, HubSpot, Groq, and Monday.com — Exa has positioned itself as serious infrastructure, not a hobby project. SOC 2 Type II, SSO, and Zero Data Retention options are available on enterprise tiers. For builders who need a search tool call inside an agent and want neural retrieval as a first-class feature, Exa is one of the strongest picks.
Pricing is per-call and can stack up on agentic workloads that issue many searches per task — set rate limits and cache aggressively. Neural search quality depends on phrasing; keyword fallback exists for a reason. Index coverage on very fresh news (last few hours) and non-English content is thinner than Google.
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