CONTENT CREATION

Produce localized hero-image variants with embedded captions

On request, takes a base product screenshot from Drive, generates localized caption overlays, renders a hero-image variant per locale.

CategoryContent Creation
Enginesim
Difficultyadvanced
Triggermanual
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerManual run with base image and locales
  • ActionRead base screenshot from DriveGoogle DriveGoogle Drive
  • ActionWrite localized captions and alt-textOpenAI
  • ActionRender hero variant per localeImage generation
  • LogicVerify each variant rendered
  • OutputSave variants and alt-text to DriveGoogle DriveGoogle Drive

What it does

Turns one base product screenshot into a set of locale-specific marketing hero images. It writes a localized caption for each target market, renders a branded hero variant with that caption baked in, attaches matching alt-text, and saves every variant into a structured Drive folder ready for the web team.

When to use it

Use it when a single screenshot needs to ship as polished, captioned hero art across multiple regions and you don't want a designer to hand-build each locale. Good for landing-page heroes, app-store galleries, and paid-social creative that must look native in every market.

How it works

  1. 1A manual run kicks off with a chosen base screenshot and locale list.
  2. 2The flow reads the base image from Google Drive.
  3. 3OpenAI writes a localized headline caption and alt-text for each target locale.
  4. 4The generate-image step renders one hero variant per locale with the caption composited onto the screenshot.
  5. 5A logic step verifies each rendered variant exists before delivery.
  6. 6All variants and their alt-text are saved to a locale-organized Drive folder.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect Google DriveDocs, sheets, slides, files.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect Image generationManaged Nano Banana image renders, metered per image.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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