ROME-- May 03, 2023 -- Translated, a global leader in language translation, has announced a significant expansion of its machine translation services. Previously supporting 56 languages, the company’s adaptive machine translation technology, ModernMT, now supports 200 languages, setting a new benchmark in the industry. No other commercial service currently supports such an extensive range of languages.

Translated’s ModernMT was recently recognized as a leader in machine translation by both IDC and CSA Research, further demonstrating its high quality and reliability. By expanding its language coverage to potentially reach 6.5 billion native speakers, Translated empowers enterprises to forge stronger connections with global users and customers, enabling seamless communication and understanding.

Effective today, enterprises can now access the new offering via an API, and professional translators can benefit from the expanded language support using a plugin for their Computer-Assisted Translation (CAT) tools, such as Matecat. The adaptive models are designed to continuously improve translation quality by incorporating corrections from professional translators in real time.

For the first time ever, 30 new languages are supported in the market, leapfrogging directly to the most capable adaptive technology. Among the new languages now supported by ModernMT are Bengali, Punjabi, and Javanese, helping us reach over 2 billion more native speakers worldwide. This significant expansion has been made possible thanks to the exponential growth of research in AI and the efforts of non-profit organizations like Common Crawl&& and Opus, in addition to the transparency of Meta's language research.

Marco Trombetti, CEO of Translated, commented on the company's milestone: “Today, we are not merely providing a tool that supports translation in more languages. Our adaptive models empower professional translators to handle more content, while their corrections contribute to the continuous enhancement of machine translation quality across these languages. We believe this collaborative approach will aid in increasing translation quality and help preserve many endangered languages, showcasing a powerful and sustainable synergy between humans and machines.”