Batch

Stop running things one at a time.

Batch is the production layer of Pletor.

A workflow you build in Studio runs one input at a time. Batch takes that same workflow and runs it across every input you have, in a single pass, holding the same standard on the first row and the five-hundredth.

The mental model: build the system once, run it at volume. You don't rebuild anything for Batch. Any workflow you've already encoded becomes runnable across a whole catalog — from the app, or from an agent through the Pletor MCP.

1. Open Batch mode

Two ways in:

• Click here or access Batch from your workspace nav — start a new Batch, then pick the workflow you want to run on.

• From an existing agent in Studio — switch a workflow you've already built into Batch mode directly.

Either way, you're running an existing workflow. Batch is a way to run, not a new thing to build.

2. Prepare your inputs

Each row in a Batch is one run of your workflow.

• Drag and drop a folder of files, or type inputs free form to build your set by hand.

• Brand nodes act as context — your Brand Brain applies to every row, so the whole Batch stays on-brand without per-row setup.

• Need the same value everywhere? Set one input for the whole Batch instead of repeating it row by row.

Prepare a Batch from Claude (or any MCP-compatible agent) The Pletor MCP exposes a prepare_batch tool, so an agent can assemble your inputs from data you already have elsewhere — a sheet, an Airtable, a PIM export — and hand the prepared set straight to Batch. You describe what you want batched; the agent builds the rows. No manual entry. Example: "Prepare a Batch from my Q2 top performers in Airtable, one row per SKU."

Install the Pletor MCP here

3. Run Batch

Launch the run. Every row executes your full workflow at once.

4. Production starts

Once the run begins, Batch produces assets for every row in parallel. You can leave the page; the run continues.

5. Review on the same page

When assets are ready, you review them where they were produced — no export-and-reimport loop. For each result:

• Keep what shipped

• Discard what missed

• Re-run a row, or edit it in place

Review is part of the run, not a separate step. That's what makes a Batch a system instead of a backlog: you run at volume and keep control of every output in one place.