Long before I’d ever heard the term ‘continuous localization’ I was already very familiar with the problem it’s meant to solve. I spent years working as an iOS developer before I moved into product. At the time, localization wasn’t my main job but it became one of the many things competing for my attention. Some […]

How well can you map your MT and AI spend to the value it’s creating? You already know what that spend costs. What’s harder is connecting it to what your company actually cares about: whether a market grew, whether a campaign drove revenue, whether the investment was worth it. Phrase Data closes that gap now. […]

Something has quietly changed in the relationship between businesses and their customers over the past few years. Businesses could once assume that the friction of switching providers and the effort required to find a credible alternative would make customers more willing to tolerate a disappointing experience. The change has not been dramatic, but it is steadily removing a layer of protection that many business models still depend on.

The best market launches are the ones you forget happened.  No last-minute translation scramble and no war room…just a new locale going live roughly on time while the team gets on with the next thing. Call it the non-event: localization that ships without anyone noticing it did. For product managers running global products, that’s the […]

Building on Part 1's case against the post-editing paradigm, Alon Lavie outlines a new model for human-AI collaboration in translation. Today's LLMs make it possible to rethink translation as an adaptive, interactive process where human experts steer AI systems rather than correct their output. The technology is advancing fast, but the bottleneck remains systems integration

Every global company has the meeting: a campaign lands at home and falls flat everywhere else. The instinct is to fix the translation. The real problem started much earlier. Here's what the most internationally mature companies are doing instead.

MQM was the most robust answer we had for human evaluation. Automated evaluation is a different problem, and the seams are starting to show.

When AV runs outside your TMS, terminology drifts and consistency breaks down. Phrase Studio closes that gap by running subtitling, dubbing, and voice-over inside the same workflow your text content already uses.

Most announcements work like this. A company describes what it intends to build, frames it as a vision, and asks you to believe the future they're describing. This post is different (and longer than most!).