One approved design.
Every required version.
Fill a template from CSV or JSON, validate rows independently and track every result without losing the batch context.
JsonCut bulk rendering turns structured input rows into independent image or video jobs with visible partial success.
CSV + JSON
Row validation
JsonCut bulk rendering turns structured input rows into independent image or video jobs with visible partial success.
Catalog variants.
JsonCut bulk rendering turns structured input rows into independent image or video jobs with visible partial success.
Enough control for real work.
Only when you need it.
Fill a template from CSV or JSON, validate rows independently and track every result without losing the batch context.
Use CSV or a JSON array
Map a familiar dataset to the template contract without rebuilding the approved project for each row.
Reject bad rows before rendering
Missing values, invalid types and unavailable media remain row-specific and actionable.
Let valid work continue
Independent jobs preserve partial success instead of making one problematic row discard the complete batch.
Connect each output to its source
A result manifest keeps identifiers, status and downloadable outputs associated with the input row that produced them.
What makes bulk rendering useful in real work.
Each capability remains connected to the same editable JsonCut project.
Validate before spending
Input types and required fields are checked before invalid rows enter rendering.
Keep failures isolated
One bad record does not discard successful work from the same batch.
Follow the whole operation
Searchable job status and manifests connect each source row to its output.
Use CSV or a JSON array.
Connect each output to its source.
Use CSV or a JSON array
Map a familiar dataset to the template contract without rebuilding the approved project for each row.
Reject bad rows before rendering
Missing values, invalid types and unavailable media remain row-specific and actionable.
Connect each output to its source
A result manifest keeps identifiers, status and downloadable outputs associated with the input row that produced them.
Catalog variants.
And the work after it.
Know what the feature changes.
01Is this available in both image and video projects?
The page states where a capability applies. Shared controls use the same visual language in both editors.
02Does it remain editable after using AI?
Yes. The assistant changes ordinary project layers and versions, so you can inspect and refine the result.
03Can the same result be automated?
Yes. Projects can become typed templates or be rendered through the focused V2 API and MCP surface.
See the control.
Keep the result editable.
Start a free project and use the same feature in the image or video workflow it belongs to.
Start creating free