SYSTRAN: Use-Cases, Insights and Reviews | 2026 Cuspera

Nestlé needed to translate and localize content in many languages for different uses. Their old process used only human translation, which was slow and costly. They chose SYSTRAN's machine translatio...n server for 3,000 users to translate in 32 languages. The solution helped them process more translation work, lower costs, and keep content private. Nestlé used the tool for technical and legal documents, with both automatic and human-edited translations.
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Stellantis wanted to help its employees around the world communicate better. They needed a translation tool for their Intranet Portal that was secure and easy to use. Stellantis chose SYSTRAN's machi...ne translation solution and added it to their IT system. Now, 3,000 users each day can translate documents and emails in real time. The tools help create multilingual content and keep information safe. Since launch, users make 40,000 to 50,000 translation requests daily, and the dictionary service saw a 112% increase in use.
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Ariel Corporation wanted to get more value from their language assets. They used XTM and SYSTRAN to improve their translation process. Their content management system worked well with XTM. Adding SYS...TRAN made the process even better. They saw a 22 BLEU point increase in translation quality. They also reduced costs and improved translation quality on new content.
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Petit Futé wanted to expand its travel guides to new foreign markets. They faced a challenge because their content was very large and changed often. They needed a way to translate this content quickl...y and affordably. Petit Futé chose SYSTRAN’s automatic translation technology. They used it to translate practical information and help their translators work faster. The solution was fully integrated into their system. This helped them launch an English website and support more languages.
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New Paradigm needed a better way to translate large amounts of sensitive data in many languages. They wanted to save analysts' time, customize language profiles, and keep data secure. They chose SYST...RAN over other options for its strong technology and support. SYSTRAN's on-premise solution gave them better data privacy and efficiency. Now, they translate about 16 million posts per month, up from just 200 before. Their team can now focus on risk reporting instead of manual translation.
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FARFETCH needed to localize large amounts of content for its online marketplace in 16 languages. Their translation process was manual and slow. They started using a translation management system, but... it was not enough for their high volume. They then added SYSTRAN's neural machine translation to their workflow. This change led to a 30-35% improvement in efficiency and a 35-45% reduction in costs. FARFETCH also saw an extra 10-15% gain in the second year by retraining the translation engine.
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