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There’s no getting around it—the localization industry is ripe for a shakeup, and it’s not only AI that’s doing the shaking. From geopolitics to new regulations, the way we help companies communicate changed throughout 2025, and the business decisions behind those changes are moving just as quickly. At Argos, we think it’s just as important […]

Let’s talk about hiring. An AI screening tool reviews two resumes. One is in English and one is in Spanish. Both candidates have the same qualifications, yet only the English one moves forward. Nothing in the interface calls attention to a problem. The model isn’t trying to discriminate – it’s repeating the patterns it learned […]

Localizing images has never fit neatly into standard workflows. Screenshots, graphics, and UI flow images contain text that translation tools can’t read, so teams handle them as separate tasks that take extra time and coordination. MosAIQ ImVisio creates a simple, scalable workflow for visual assets using automated image translation and structured review. The AI-powered tool […]

Ask Better Questions: Solutions Design in a Complex World Join Stephanie Harris-Yee and Erik Vogt for an in-depth exploration of Solutions Design and its critical role in today’s rapidly evolving localization landscape. Erik shares insights from his LocWorld presentation on how strategic thinking and systems design are transforming the way we approach multilingual content challenges. […]

Multimedia localization once focused on language, layout, and timing. As of 2025, it also has to meet digital accessibility standards. With the EU Accessibility Act now in force, organizations are expected to make every digital asset, from videos and training programs to internal communications and eLearning courses, part of a broader accessible multimedia strategy. That […]

Between October 14 and 16, the Argos Multilingual team once again traveled to the marquee industry conference, LocWorld54, in cool, sunny Monterey. Another conference on the circuit, another strong showing for our team, and an event packed with learnings and experiences. As before, we bring you the short and long of it, in case you […]

Behind every smart AI system lies an enormous amount of teaching. Before it can spot patterns or make predictions, someone has to show it what to look for by providing thousands, or even millions, of examples. Those examples only become training material once they’re labeled and structured, a step called data annotation. Think about self-driving […]