Overview
You can now process thousands of cards and records at once through the Pipefy Piece, without building loops to handle each item individually inside a flow. The new batch operations cover both sending data into Pipefy and exporting information from a pipe or database into a single file, making integrations, migrations, and initial data loads much faster.
What's new?
- Batch Upsert: send a CSV or JSON file to create or update thousands of cards or records in a single operation. Use up to 3 combined fields to identify existing items, or match by ID or title, and choose whether unmatched items should be created or skipped.
- Batch Export: export all cards from a pipe or records from a database into a single CSV or JSON file. Use a saved report or an advanced filter to define what gets exported, and choose which columns are included.
- Processing tracking: track the status of each batch operation and access a row-level error report, reprocessing only the rows that failed without re-uploading the whole file.
- Wait for batch completion: use this when the next steps in your flow need the final processing results before continuing.
- Duplicate protection: operations use an idempotency key to prevent duplicate submissions or exports.
How does this help?
- Less complexity in your flow: you no longer need to build loops to process items one by one, cutting down executions and simplifying logic.
- Faster migrations and initial loads: files up to 50 MB and thousands of rows per batch let you bring in large volumes of data at once.
- Error recovery without rework: the row-level report lets you fix and reprocess only what failed, without resending the entire file.
- Exports ready for the next step: the file generated by Batch Export can feed directly into another flow step, such as sending an email, storage, or even another Batch Upsert.
Use cases
1. An HR agent in an employee onboarding flow who needs to migrate the employee base from a legacy system into Pipefy. Instead of creating one card at a time, they export the spreadsheet from the old system, map the name, email, and hire date fields, and use Batch Upsert to create all the cards at once, matching by email to avoid duplicates if the file is resent. The agent no longer has to open hundreds of cards manually or ask IT to run an import script.
2. An Operations team in a financial reconciliation flow that receives a daily file from the ERP with the payment status of thousands of invoices. Instead of updating cards one by one, the team uses Batch Upsert with ID matching to update the status field of every invoice at once, covering approved, pending, and rejected payments. The team no longer depends on manual updates or item-by-item routines that used to take hours to clear the day's batch.
3. A Builder responsible for a purchasing audit flow who needs to generate monthly reports with every card from a purchase request pipe. Instead of exporting manually through the interface, the flow uses Batch Export with a saved report to generate a CSV with vendor, amount, and category columns, automatically passing the file to an email step for the finance team. No one needs to log into Pipefy at month end to pull this report by hand.
4. An integration agent in a customer initial load flow during the rollout of a new process, receiving a base of thousands of accounts from a CRM system. When running Batch Upsert, some rows fail due to blank required fields. The flow uses the row-level error report to pinpoint exactly which accounts failed, allowing those rows to be fixed and reprocessed without resending the entire base. The implementation team doesn't waste time rebuilding the load file from scratch.
Most relevant for
- Operations teams
- Builders working on integrations
- Implementation and data migration teams
- IT Leaders
Plans and availability
Batch operations are being rolled out gradually. If they don't appear for you yet, contact the Pipefy team to request enablement. To use Batch Upsert and Batch Export, the connection used in the Pipefy Piece must be a Service Account.
