Exa is an AI-native search engine and infrastructure platform designed specifically for the needs of AI agents and automated workflows. Unlike traditional search engines that are optimized for human consumption, Exa provides a robust API-first search architecture that delivers high-quality, structured information, allowing AI systems to retrieve, process, and ground their output in real-world data at scale. The platform enables developers to perform complex research tasks, build structured data lists, and maintain constant awareness of specific information streams.

Functionality centers on providing specialized search, content extraction, and agentic research capabilities. It handles everything from simple queries to deep, multi-step research processes that return machine-readable JSON, summaries, and cited highlights. The platform is designed to minimize token usage for LLMs while maximizing the precision of the information provided, making it an essential backend for modern AI applications.

Some of the key features are:

• AI-Native Search API: High-performance search specifically tuned for AI model consumption, providing sub-200ms latency for rapid retrieval.
• Structured Data Extraction: Ability to return content as clean, schema-validated JSON, reducing the need for post-processing and improving LLM reliability.
• Agentic Research & Enrichment: Advanced capabilities for multi-step tasks, such as building company databases, finding decision-makers, and automating multi-hop research workflows.
• Token-Efficient Highlights: Specialized extraction of relevant passages from web pages, designed to drastically reduce token counts for LLM integration.
• Persistent Monitors: Scheduled search and extraction that tracks changes and updates over time, delivering fresh information directly via webhooks.
• Comprehensive Web Crawling: Robust infrastructure for crawling and parsing modern web content, including JavaScript-rendered pages and complex document structures.
• Enterprise-Grade Security: Features including SOC 2 Type II compliance, configurable Zero Data Retention (ZDR), and robust SSO integration for team management.

Operationally, Exa is integrated through a developer-friendly API available via Python, TypeScript, and standard REST requests. Developers can invoke specific search types, request custom output schemas, or trigger autonomous agent runs. For advanced workflows, the system supports streaming events, allowing developers to track the lifecycle of an agent's research from queueing to completion. It is built to support massive concurrency, scaling to serve thousands of searches per second for production-grade applications.

Some common use cases include:

• Agentic Lead Generation: Automating the process of identifying companies, finding key decision-makers, and enriching CRM records with real-time financial or funding signals.
• Coding Agent Grounding: Providing technical documentation, code repositories, and research papers as context to specialized coding assistants.
• Competitive Intelligence: Monitoring competitors through scheduled searches that alert teams to product launches, funding milestones, or regulatory updates.
• Research Automation: Empowering scientific and knowledge-work agents to gather vast amounts of information, extract specific metrics, and summarize findings into structured reports.