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Exa AI

The search engine built specifically for AI, allowing LLMs to retrieve accurate, structured web data.

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Coding Productivity

Best For

AI Engineers Data Scientists Developers

Pricing

Freemium

Platform

API

Developer

Exa AI Inc.

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About Exa AI

Exa (formerly Metaphor) is a search engine architected specifically for AI agents and Large Language Models (LLMs). Unlike traditional search engines designed for humans (keyword matching), Exa uses a neural search approach based on embeddings, allowing it to understand the semantic meaning of queries and retrieve high-quality, relevant results.

The platform provides an API that enables developers to connect their LLMs to the live web, facilitating 'Retrieval Augmented Generation' (RAG). Exa can return clean, parsed HTML content, filter results by date or domain, and find 'similar' pages, making it a critical infrastructure component for building intelligent, up-to-date AI applications.

Key Features

  1. Neural Search: Uses embeddings to find semantically relevant results rather than just keyword matches.,
  2. Clean Content Extraction: Returns cleaned, full-text content from webpages, optimized for LLM consumption.,
  3. Similarity Search: Find URLs that are semantically similar to a provided link.,
  4. Powerful Filters: Filter search results by domain, date range, and content type.,
  5. API-First Design: Built primarily for programmatic access by AI agents and developers.

Use Cases

  1. Building RAG (Retrieval Augmented Generation) pipelines for chatbots.,
  2. Automating market research agents that need to find companies or products.,
  3. Creating curated news feeds by filtering for high-quality recent articles.,
  4. finding training data for specific niche topics.

How to Use

  1. Sign up for an API key at exa.ai.,
  2. Install the Exa SDK (Python/Node.js) or make HTTP requests.,
  3. Send a search query via the API (e.g., "Find the best technical blog posts about React").,
  4. Receive a JSON response with URLs and cleaned content.,
  5. Feed the retrieved content into your LLM context window.

Pros

  1. Significantly better than Google Search API for LLM use cases.,
  2. Returns clean content, saving developers from building custom scrapers.,
  3. 'Search by meaning' enables finding resources that keyword search misses.

Cons

  1. Primarily a developer tool; no consumer-facing chat interface.,
  2. Pricing is based on API usage, which can scale with high volume.

Tags

AI Search Engine API Developer Tool LLM Tool RAG

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