Exa

What is Exa AI

Exa AI is a web search API and AI web researcher that delivers fresh, high-quality results from across the public web to power your applications. It combines business-grade search, large-scale crawling, and LLM-ready answers so you can discover, collect, and enrich data in real time. With features like Websets for curated corpora, domain and freshness filters, and source-level citations, Exa AI helps teams build reliable RAG pipelines, automate competitive research, and turn open web content into structured, actionable insights.

Exa AI Key Features

• Web Search API: Query the live web with relevance ranking, freshness controls, and domain filters to retrieve high-signal results suitable for downstream ML and analytics.
• Crawling at scale: Fetch and parse target pages to extract full text and metadata, enabling dataset creation and continuous enrichment.
• LLM Answers: Get concise answers grounded in Exa search results, with citations that help you verify and attribute sources.
• Websets: Build curated collections of sites or documents, keep them updated, and use them as a focused corpus for search, enrichment, and RAG.
• Structured outputs: Receive clean JSON with URLs, titles, snippets, and content, simplifying ingestion into data pipelines and vector databases.
• Real-time discovery: Access fresh, relevant web data for time-sensitive tasks like news tracking, market monitoring, and research.
• Enterprise-grade controls: Configure queries, filters, and quotas to balance precision, coverage, and cost in production workloads.
• RAG-friendly: Easily ground prompts with retrieved passages and attach source links for transparent, auditable responses.

Who is Exa AI for

Exa AI is ideal for data engineers, ML engineers, and product teams building retrieval-augmented generation systems; researchers and analysts doing market, competitive, or academic research; growth and SEO teams tracking content and trends; and sales operations teams enriching leads with verified website data.

How to Use Exa AI

1. Sign up and generate an API key in your Exa AI account.
2. Choose an endpoint: Search for discovery, Crawl for full-page extraction, or LLM Answers for grounded responses; optionally create a Webset to scope results.
3. Define your query or seed URLs, apply filters (domain, freshness, language where applicable), and set result limits.
4. Call the API from your app or notebook, parse the JSON response, and store content in your warehouse or vector database.
5. For RAG, select top passages, add citations, and condition your model prompts on retrieved context.
6. Schedule periodic searches or crawls to keep datasets current, and monitor usage, latency, and error metrics.

Exa AI Industry Use Cases

Product teams build customer-facing search and RAG features by curating a Webset of documentation, blogs, and forums, then grounding model outputs with cited sources. Strategy and research groups track competitors and markets by running scheduled searches and crawls to monitor updates, press, and pricing pages. Sales ops enrich lead lists with company descriptions and product signals directly from websites. E-commerce teams expand product catalogs by extracting specs from manufacturer pages. Journalists and analysts surface timely, attributable sources for reporting and briefings.

Exa AI Pros and Cons

Exa AI FAQs

• Q1: How is Exa AI different from a general search engine?

  Exa AI is API-first, returns structured results, offers fine-grained filters, supports curated Websets, and provides LLM-grounded answers with citations for direct use in apps and pipelines.

• Q2: Can I use Exa AI for RAG?

  Yes. Retrieve passages via the Search or Websets workflow, embed or index them, attach source URLs, and condition your prompts on these passages to improve accuracy and trust.

• Q3: Does Exa AI provide citations?

  Results include source URLs and metadata so you can attribute, verify, and display links alongside summaries or answers.

• Q4: What types of data can I crawl?

  You can target public web pages relevant to your use case and extract text and metadata for enrichment, analysis, or indexing.

• Q5: How fresh is the data?

  Exa AI supports real-time discovery and scheduled updates; freshness depends on your query settings, Webset configuration, and update cadence.

• Q6: Is there a UI, or is it API-only?

  The service centers on APIs for integration into your stack; teams can also manage curated corpora and workflows using Websets.