Exa

Exa is a meaning-based web search API designed for AI agents and developers. Instead of returning results purely from keyword matching, Exa retrieves highly relevant web context using embeddings, with options to return links, highlights, summaries, and structured outputs (depending on the request).

Teams commonly use Exa for research workflows like finding recent product or topic updates, building web-grounded answers with citations, and extracting targeted information from pages for downstream processing—especially when you want results that are easier for AI systems to use than raw links alone.

Use Cases

Research briefs with supporting context

Use Exa to retrieve the most relevant web context for a topic, then have Fetch Hive process and summarize it into a brief your team can share. When structured outputs are available, you can also turn returned fields into reusable content blocks.

Fact-checking and source comparison

Use Exa to pull context for specific claims and compare what different sources say. Fetch Hive can then consolidate the evidence into a single, traceable output so reviewers can see what was retrieved and why the final summary looks the way it does.

Company and topic monitoring (on demand or recurring)

Use Exa to retrieve updated information for a set of companies, technologies, or market themes. Fetch Hive can log each retrieval, track the workflow cost, and route results into reports, dashboards, spreadsheets, or internal workflows for follow-up.

Why use Exa with Fetch Hive?

Instead of using Exa as a one-off search tool, Fetch Hive turns it into repeatable work: you can run the same search-and-summarize process consistently, inspect detailed trace logs for every step (including what happened and what failed), and track every workflow’s cost. Because Exa supports parallel execution in Fetch Hive, teams can process many queries, feeds, records, or data points faster without checking each one manually. The retrieved results can also be sent into your reporting or operations flow—like alerts, spreadsheets, briefs, dashboards, or internal routing—so research becomes an input to action.

FAQ

What is Exa used for?

Exa is used to retrieve meaning-based web search results and web context that AI systems can consume—often with summaries, highlights, or structured outputs depending on what you request.

What kind of outputs can Exa return for AI workflows?

Exa can return things like links, page content views such as highlights, AI-friendly summaries, and structured outputs when you request them, depending on the call type and returned data.

How does Fetch Hive make Exa easier to use for recurring work?

Fetch Hive lets you package Exa retrieval plus downstream processing (summarize, analyze, format, and route outputs) into a repeatable workflow, with full trace logs and cost tracking so you can debug and improve over time.

Can I use Exa inside Fetch Hive workflows?

Yes. Exa is available as a Fetch Hive workflow step, so you can retrieve results from Exa and then process the returned data in later workflow steps.

Does Fetch Hive log what happened and what it cost for Exa runs?

Yes. Fetch Hive records detailed trace logs for workflow execution and logs costs for workflows/runs, so you can see what succeeded or failed and understand spend tied to each run.