Flows

Running flows in batch

Execute Flows across multiple inputs simultaneously using batch processing. Useful for bulk operations, testing, and data processing tasks.

When to use batch processing

  • Bulk operations: Process hundreds or thousands of items
  • Testing: Run Flows against a dataset to verify behavior
  • Data migration: Transform or enrich existing data
  • Evaluation: Compare Flow performance across many inputs

Running a batch

Batch execution runs your Flow once for every Record of a chosen type.

  1. Open the Flow
  2. Click Run
  3. Select the Batch tab
  4. Choose the Record Type to run against
  5. Click Start Batch

Each Record of that type becomes one Flow execution, with the Record’s fields available to the Flow as input variables.

Getting data into a batch

The dashboard runs batches over Records, so to batch-process external data you import it as Records first:

  1. Go to the Records page and import or create the Records you want to process. The Records import accepts a CSV file.
  2. Return to the Flow, open the Batch tab, and select that Record type.

If you need to submit inputs programmatically rather than from saved Records, use the batch API instead of the dashboard.

Monitoring batch progress

After starting a batch:

  1. Go to Logs → Batch Jobs
  2. Find your batch execution
  3. See:
    • Total items
  • Completed count
  • Failed count
  • Progress percentage
  • Estimated completion time

Batches run in the background—you can close the browser.

Batch results

After completion, download results:

  1. Go to the batch job page
  2. Click Download Results
  3. Choose format:
    • CSV (inputs + outputs)
  • JSON (full execution details)

CSV includes all input columns plus an output column with the Flow result.

Handling failures

If some items fail:

  1. Download the failed items CSV
  2. Review error messages
  3. Fix issues (update Flow or data)
  4. Re-run the batch with only failed items

See Handling batch failures for detailed troubleshooting.

Batch limits

Batch size and concurrency limits depend on your plan tier. For large batches, split into smaller batches to make monitoring and error recovery easier.

Cost considerations

Batch processing can consume significant AI credits:

  • Each item counts as one Flow execution
  • 1,000 items = 1,000 executions
  • Monitor usage to avoid surprise bills

Use smaller models (e.g., gpt-5.4-mini) for batch operations when possible.

Scheduling batches

Automate batch processing with schedules:

  1. Go to Schedules
  2. Create a schedule
  3. Select your Flow
  4. Configure to run against a Record collection
  5. Set frequency (daily, weekly, etc.)

See Automating batch processing for details.

Best practices

  • Test with small batches first: Run 10-100 items before scaling to thousands
  • Monitor costs: Check usage estimates before starting large batches
  • Handle failures gracefully: Design Flows to fail gracefully on bad input
  • Use appropriate concurrency: Higher concurrency is faster but can hit rate limits
  • Save results: Download and archive batch results for auditing

Next steps