Exa is a search engine built specifically for AI. Instead of returning links optimized for human clicks, Exa delivers clean, semantically relevant results that AI agents and LLMs can use directly. It supports neural search, keyword search, content extraction, a find-similar endpoint, and an agentic research API. Developers use Exa to power RAG pipelines, AI chatbots, research tools, and lead generation workflows.

• Neural Semantic Search: Goes beyond keyword matching to understand the meaning behind queries using transformer-based embeddings, returning results that match intent even when wording differs.
• Clean Content Extraction: Returns parsed, clean HTML and text from web pages, not just links. Ideal for feeding directly into LLM prompts and RAG pipelines.
• Highlights (Token-Efficient Retrieval): Condenses full web pages into only the tokens an LLM needs, reducing costs and improving retrieval quality for RAG applications.
• Find Similar: Provide a URL, and Exa returns pages that are semantically similar in meaning, useful for competitive analysis and content discovery.
• Exa Research (Agentic Search): An agentic search engine that automates iterative querying, reading, clustering, and summarization for in-depth research tasks.
• Category-Specific Search: Supports specialized search categories such as companies, people, research papers, GitHub repositories, financial reports, PDFs, and news sources.
• Websets (No-Code List Building): A no-code interface for building enriched lists of companies and people using natural language queries, complete with email, funding, and category data.
• Broad SDK & Integration Support: Python and JavaScript SDKs, plus native integrations with Vercel AI SDK, LangChain, CrewAI, LlamaIndex, Anthropic/OpenAI tool calling, and MCP for Claude.

• High Semantic Relevance: Users consistently report that Exa returns more contextually accurate results than competitors like Tavily or Brave Search API, especially for complex natural language queries.
• Developer-First Design: API-first architecture with full control over retrieval parameters, search modes, domain filters, and date filters makes it easy to integrate into any AI workflow.
• Flexible Search Modes: Offers multiple latency-quality profiles, from 200ms instant search for chatbots to 60-second deep search for thorough research.
• Strong Entity Coverage: Specialized indexes for people, companies, and research papers provide structured data that general search engines miss.
• Simple Integration: Described by users as "dead simple to integrate," with just a few lines of code needed to add web search to AI applications.

• Variable Pricing Can Add Up: Costs depend on result count, content inclusion, and query depth, which makes budgeting harder compared to flat-rate competitors.
• Not a Consumer Search Engine: Exa is built for developers and AI systems, not for general web browsing or casual search.
• Learning Curve for Advanced Features: Semantic search modes, filtering options, and retrieval tuning can be complex for developers new to AI search infrastructure.
• Struggles with Multi-Step Precision Tasks: While the research agent handles broad exploration well, it has shown limitations with precise, multi-step retrieval tasks in comparative testing.

• RAG Pipelines and AI Chatbots: Feed your LLM real-time, relevant web content instead of relying on stale training data. Exa's content extraction and highlights features return only the tokens your model needs, reducing hallucination and lowering API costs.
• Automated Research and Report Generation: Use Exa Research to automate the full research loop: querying, reading, clustering, and summarizing sources. Teams use it for market research, competitive analysis, and building briefs with cited sources.
• Lead Generation and Sales Prospecting: Use Websets to type natural-language queries like "AI-first SaaS companies hiring backend engineers in Spain" and get enriched results with emails, funding data, and company categories in seconds.
• Company and People Discovery: Search Exa's specialized indexes to find companies by funding stage, industry, and location, or find professionals by role and employer. Useful for investors, recruiters, and business development teams.
• AI Agent Web Access: Give your autonomous AI agent the ability to search the web mid-conversation. Exa's low-latency, structured output is designed for machine consumption, making it the retrieval layer for tools like Cursor and Notion AI.
• Code Search and Developer Tooling: Search GitHub repos, StackOverflow threads, and technical documentation for code examples, API syntax, and debugging help. Exa's MCP server connects directly to AI coding assistants.