Expanding internationally without a large translation team: that is what AI-assisted multilingual content production makes possible. But the approach matters more than the technology. Here is what a launch in seven languages looked like.
A software company wanted to launch its product simultaneously in seven European markets. The available content team consisted of three people. Hiring professional translators for all languages would delay the launch by six months. Choosing AI-assisted translation with localisation made a simultaneous launch possible.
The content requirement for the launch was considerable: a fully localised website (around 80 pages), onboarding materials for new users (15 documents), marketing materials for each channel and customer service FAQs per market.
In total, approximately 120,000 words of content needed to be available in seven languages: English, German, French, Spanish, Italian, Swedish and Dutch. With traditional translation and review: six months of work. With AI support: six weeks.
The first and most important choice was distinguishing between translation and localisation. Translation converts text from one language to another. Localisation adapts content to the cultural and commercial context of a specific market.
For the core pages of the website and marketing materials, localisation was needed, not translation alone. That meant:
Step 1: Optimise source text: before AI translated the text, the source content was reviewed for constructions that translate poorly: idioms, long sentence structures, culturally bound humour. A clean, clear source text leads to better AI translations.
Step 2: AI translation: the translation model (in this case DeepL combined with GPT for editing) translated the optimised source text into all seven languages.
Step 3: Local review: for each language, one native speaker was hired as a freelancer for a review round. This person did not assess every sentence, but focused on critical pages: homepage, product pages, pricing page and onboarding.
Step 4: Terminology management: a shared glossary of brand-specific terms, product names and technical terms ensured consistency across all translations.
The approach worked particularly well for informational content: FAQs, help articles, user documentation. AI translation of this type of content required minimal human correction and delivered quality comparable to a professional translator.
The time savings were considerable: six weeks instead of six months for the complete content set.
The marketing texts for the German-speaking market had to be almost entirely rewritten. The AI translation was grammatically correct but lacked the direct, business-like tone common in the B2B market in Germany. The freelance reviewer flagged this early, allowing timely correction.
For Italian, there were problems with the translation of technical product terminology: the model sometimes chose generic terms rather than accepted industry standards. An expanded glossary resolved most of this.
After launch, a maintenance process was needed for updates. Every change to the source text had to be applied in all seven languages. This was partially automated: when changes were made, the system automatically generated new translations that entered a review queue.
A multilingual launch in seven languages simultaneously is achievable with a small team if the approach is properly set up. The difference lies not in the quality of the AI model, but in the preparation: clean source texts, a good glossary and local review for critical content.
Mach8 helps organisations with multilingual content production using AI. View our multilingual content service or get in touch.
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