Languages and Localization

Language and number formatting are set per catalog — the locale drives what language Aimée writes in and how prices are displayed in generated ad creative.

Updated July 1, 2026

Language isn't a single account-wide setting — it's configured per catalog, because different catalogs often represent different stores, markets, or storefronts with different customers.

Locale and fallback languages#

Each catalog has:

  • A primary Locale — set when the catalog is created, and editable afterward.
  • One or more Fallback languages, in order.

The locale drives the language Aimée writes in — ad copy, headlines, and other AI-generated text default to the catalog's locale. If you write prompt instructions in a different language yourself, you can still ask Aimée to output in the product's native language — see Working with prompts.

Fallback languages matter when a specific piece of content isn't available in the primary locale — Renable falls back through the ordered list before leaving a placeholder empty.

Number and currency formatting#

Prices and other numbers can be rendered with a specific thousands separator, decimal separator, and number of decimal places, independent of however your raw feed formats them — useful when your feed exports numbers in one regional format but your ad creative needs another.

This isn't set on the catalog page itself — it's configured in Studio, on any placeholder bound to a Number field (Properties → Placeholder → Number format, showing Thousands separator, Decimal separator, and Round to decimals). See Placeholders for how placeholder binding works.

Editing the number format on a placeholder overrides only that one placeholder. There's a catalog-wide fallback in the data model, but no current setting in the app to configure it — every other number placeholder uses the built-in default (no thousands separator, dot decimal) until you override it individually.

Which languages are supported#

Language support depends on which kind of AI feature is generating the content:

  • Extractive features — ad-copy extraction and review-fragment extraction, which run on Renable's own machine-learning models — currently support European and North American languages.
  • Prompt-based generation — ad copy, headlines, and reasons to buy written by a commercial LLM from your prompt instructions — works in essentially any language, since it relies on the underlying model's own language support rather than Renable's own models.

If you need a language you don't see working well in your generated content, reach out to support.

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