Batch Web Research With Parallel AI

For a researcher who needs N structured briefs in parallel. Creates a Parallel AI task group, launches a long-running research run per topic, monitors progress, and collects the structured outputs.

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THE GRIND

Research at scale is painful

Here's what doing this by hand looks like today — and why it doesn't scale.

Running 10 research passes sequentially takes the whole afternoon

Every brief comes back in a different shape, so synthesis is a second job

You'd batch them if there was a tool that ran parallel runs and collected structured output

Composio collapses all of this into one prompt — here's what that looks like.

THE FLOW
6 steps · 1 toolkit

Your agent runs it end-to-end.

  1. 01
    Create a Parallel AI task group for the batch
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  2. 02
    For each topic, start a research run with your structured output schema
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  3. 03
    Poll the task group until every task hits a terminal state
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  4. 04
    Fetch each completed task's structured output
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  5. 05
    Aggregate into a Google Doc or Sheet if an output target is set
  6. 06
    Return the aggregated link and per-task status
THE PAYOFF

Ten briefs at once, same structure

Launch a batch, collect structured outputs across every topic — no sequential grind, no inconsistent formatting.

Paste this into Claude, Cursor, or Codex. It'll install the CLI, connect your apps, and run the task — end to end.