Translating your webshop automatically: why a translation tool isn't a translation system
AI translates in seconds. But keeping a product catalog multilingual on a live store is something else entirely than running text through a model. Here is where the difference sits.
With today's AI models you translate a product description in seconds. Paste the text, pick the language, done. It is tempting to think going multilingual is a solved problem. In practice, that is where the work begins.
Translating is easy. Keeping a webshop multilingual isn't.
A translation tool works on loose text. A webshop is not loose text, it is a living system: products that change daily, collections that rotate, prices, variants, meta fields, SEO structures and theme components that all depend on each other. Some fields you specifically must not translate, or the site breaks or you lose your rankings. Others have to be slightly different per country, because the tone of voice in Germany differs from France.
On top of that, it runs on a live store. One wrongly translated technical field and a product page stops loading. That costs revenue immediately, there is no practice round.
What a system actually does
A translation system pulls product data from your platform automatically, knows which fields may and may not be translated, generates on your brand voice in every language, lets a human review where needed, and publishes back without breaking anything. And it does not stop after the first translation run: new products, new collections and new markets flow through it automatically.
Those figures come from ETQ Amsterdam, where we brought the complete storefront, 400+ products, into 12 languages on brand voice. The difference was not whether AI could translate, but everything around it: the fields, the review flow, the publishing and the fact that it had to keep running flawlessly for months.
A system is never finished
Models update, content changes, you open new markets. A tool you run once goes stale. A system that runs alongside your operation gets sharper every month. That distinction, between a prototype that works once and a system that runs on a live store for years without breaking anything, is where the hundreds of edge cases sit that you do not see upfront. We have already hit those, on our own stores, not on yours.
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