Exa

Exa is a search API built specifically for AI agents rather than human browsing — the core insight is that agents don't need a full webpage rendered, they need the specific, relevant piece of information extracted and formatted for a model to consume cheaply and reliably. Where a general-purpose search API returns links and snippets meant for a person to click through, Exa is designed to sit inside an agent's tool-calling loop directly. Its signature feature is token-efficient highlights: rather than returning full-page content, Exa extracts the most relevant excerpts from a page, cutting token usage by up to 90% compared to passing full-page content into a model — a meaningful cost and latency difference at scale, since token consumption is one of the largest ongoing costs for production AI agents. It also supports structured outputs, letting a developer specify a custom JSON schema and get organized data back — company details, executive names, founding dates — extracted directly from unstructured web content rather than requiring separate parsing logic downstream. Two distinct search modes let developers trade off speed versus depth: a fast-results mode for latency-sensitive applications and a deep-research mode for more comprehensive queries. Who it's for: developers building AI agents and applications that need real-time web grounding — from coding assistants like Cursor to larger enterprise integrations at companies including HubSpot, Databricks, and AWS — for both lightweight research lookups and more complex, structured data-enrichment workflows. Strengths: genuinely fast response times (under 180 milliseconds, according to the company's own benchmarks, positioned as faster than competitors like Perplexity and Brave), strong accuracy on published benchmarks (54.4% on FRAMES), broad indexed coverage including 70 million-plus organizations and specialized verticals like code search and people search, and enterprise-readiness via SOC 2 Type II certification, zero-data-retention options, and SSO. Limitations: as an API-first, developer-facing product, it isn't a consumer search tool — there's no general public-facing search interface comparable to Google, and evaluating it well requires actually building against the API rather than just browsing a marketing page. Structured extraction quality, like any AI-driven parsing, still depends on how well-formed the source content is; genuinely messy or JavaScript-heavy pages can still produce incomplete extractions. Real-world use cases: a coding assistant using Exa to pull up-to-date library documentation mid-session instead of relying on stale training data, an enterprise data team using structured outputs to enrich a company database with founder and funding information pulled live from the web, and an AI research agent switching between fast and deep-research modes depending on how thorough a given query needs to be. For teams building agents that need reliable, cost-efficient real-time web access, Exa is a purpose-built alternative to repurposing a human-facing search API.