Why Raw MT Output Can Ruin Localization feat. Alexander Murauski and Denis Zhilko

In this episode of Nimdzi Live, Alexander Murauski and Denis Zhilko discuss why using raw machine translation (MT) for localization can be a risky move. They break down how different language models (LLMs) can produce translations that vary widely in quality. Relying on these imperfect translations can lead to serious problems and poor results, especially when delivering accurate and effective content. Tune in to learn why it’s essential to carefully evaluate raw MT output before using it in your localization projects. About Aleksander: is the CEO of Alconost, with over 18 years of experience helping companies tackle translation and localization challenges. A former web developer and product manager, he also creates software solutions like Nitro, a 24/7 translation service, and Pikaban, an ad creative generator. He’s passionate about UI/UX and video storytelling. About Denis: is a problem solver who thrives on bringing order to chaos. He’s always open to meeting new people and gaining fresh perspectives. About Alconost: is a localization partner that’s been helping companies of all sizes go global since 2004. From translation and cultural adaptation to multilingual content updates and engineering, they cover it all. With support for 120+ languages, Alconost combines linguistic expertise and technology to deliver flexible, scalable solutions that fit any budget. About Nimdzi Live: There is a shadow industry driving the growth of ALL global brands: Localization. Let’s talk globalization, localization, translation, interpretation, language, and culture, with an emphasis on how it affects your business, whether you have a scrappy start-up or are working in a top global brand. Would you like to be a guest on Nimdzi Live, or do you know somebody who should? Email [email protected] or reach out to [email protected] so we can coordinate!