Turning Complexity Into a
Growth Lever

I

n this interview, Translated’s VP of Al Solutions John Tinsley explains how operational fragmentation in localization led to TranslationOS, the first adaptive Al service delivery platform for translation.

What’s the impact of Al on localization?

With the improvements in artificial intelligence, everything scaled at once: content volume, number of languages, speed expectations, and quality standards. Al reduced unit costs, but it did not simplify operations. Instead, it added new tools, new decisions, and more exceptions on top of workflows that were already fragmented. Many enterprises now move faster, but with less control and visibility.

How does TranslationOS remove complexity?

TranslationOS orchestrates Al and humans in a single transparent workflow that seamlessly integrates into existing setups or acts as the primary operating layer. The system applies the proper level of automation and human review based on business context and delivery requirements. When human review is not viable, Lara, our proprietary translation Al, helps address latent demand for translation without sacrificing trust or control.

What’s the payoff for the enterprise?

Localization stops being a bottleneck and becomes a growth lever. Teams ship faster, protect brand quality across markets, and expand into more languages with confidence. At the same time, operational overhead goes down. The entire process becomes transparent, predictable, and clearly valuable, which is exactly what enterprises need as Al moves from pilots to production.

About John

John Tinsley is the VP for Al Solutions at Translated. He’s an Irish entrepreneur, computer scientist, and translation expert. He founded Iconic Translation Machines, an award-winning language technology software business which pioneered the commercial deployment of Neural Machine Translation technology. John grew the business for almost a decade before selling it to RWS in 2020 in one of the largest technology deals in the language industry. He holds a PhD in Machine Translation and a degree in Applied Computational Linguistics, and is a regular public speaker on topics related to language, translation, and business.