CONTENT CREATION
Batch hero images from an Airtable product feed into Dropbox
Reads a product feed in Airtable, generates a branded hero image for each new product with Replicate, and files the approved renders into a per-product Dropbox folder.
How it runs
The automated pipeline, trigger to output.
- TriggerScheduled scan of Airtable for products ready for artAirtable
- ActionBuild hero prompt from product fields + brand style block
- ActionRender hero image with ReplicateReplicate
- LogicScore brand consistency; route low scores to Needs Review
- ActionFlag failing SKUs back in AirtableAirtable
- OutputSave approved render to per-SKU Dropbox folder and link the rowDropbox
What it does
Turns a structured product feed into finished hero images without a designer touching each SKU. For every product row marked ready, it builds a prompt from the product's fields, renders an image with Replicate, runs a quick brand-consistency check, and saves passing images to Dropbox while flagging the rest.
When to use it
Use it when you maintain a product catalog in Airtable and need a consistent hero shot per SKU for the store, ads, or a feed. Ideal for ecommerce or marketplace teams pushing dozens of new products a week who want art-direction baked into a prompt template instead of briefing one-offs.
How it works
- 1A scheduled scan picks up Airtable rows where Status is "Ready for art" and no hero image exists yet.
- 2For each row, the prompt is assembled from product name, category, color, and a fixed brand style block.
- 3Replicate renders the hero image at the configured aspect ratio and seed.
- 4A brand-consistency check scores the render against palette and composition rules.
- 5Below the threshold routes the SKU back to Airtable as "Needs review"; passing renders continue.
- 6The image lands in a Dropbox folder named for the SKU and the Airtable row is updated with the link.
Set it up
What you configure once, before turning it on.
- 1Connect AirtableBases, tables, views, automations.
- 2Connect ReplicateImage, video, and model inference.
- 3Connect DropboxFiles and folders.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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