Ресурсы Crowdin

This September, AI took on more of the work in Crowdin, and your organization's context now reaches the teams that translate outside it. Copilot runs scripts and builds apps without a developer, AI Pipeline can leave proofreaders only the ambiguous strings, one glossary and TM can cover every project, and teams that translate in their repository get the same Crowdin context.

A practitioner focused framework for deciding what to localize, when to localize it, and how to connect localization to real user tasks. Localization teams rarely have the luxury of translating everything at once. There is always more content waiting. New product features are being released. Documentation is changing. Marketing wants campaign pages translated. Support needs troubleshooting content. Product teams want the UI ready for a new market. Then comes the question: What should we localize first? It is tempting to answer that question by looking at what is ready for translation, what was translated last time, or which team is asking most urgently. That can create a translation queue, but it does not necessarily create a better localized experience. A more useful question is: Where does language create the most friction for our users?

Managing localization for a multi-brand global company like Sinch, a customer communications infrastructure provider, comes with complex requirements. With distinct product lines like Sinch Mailjet and Sinch Mailgun operating under the same umbrella, traditional linear translation management systems quickly became a bottleneck. They forced every piece of content through the exact same rigid review process and made it almost impossible to customize AI workflows for different content types. To fix this, Sinch teamed up with Undertow – who operates as Sinch's embedded fractional language team. Together, they moved to Crowdin Enterprise to build a modern, multi-brand localization setup – using AI not just for translation, but to manage and route workflows based on content type, while human experts focus on high-impact quality. In Q1 2026 alone, Sinch processed roughly 5 million words – surpassing their entire 2025 volume (4 million words) in just three months.

Ask a technical writer what defines their craft, and for the last two decades the answer has been simple: the how-to. Step-by-step instructions, error-free configurations, the manual that tells you exactly which button to click. That era is quietly ending. In a recent episode of The Agile Localization Podcast, host Stefan Huyghe sat down with Yaakov Simon, Documentation Manager at Cato Networks to discuss what happens to documentation when AI can already answer most "how do I…" questions on its own.

EMCD is a global crypto platform combining a mining pool, wallet, P2P exchange, and other tools for managing digital assets. As the company expanded into new markets, localization went from "nice to have" to a core part of the product experience. Victoria Franskevich is the Localization Team Lead at EMCD, with 7 years of experience in localization and project management across industries. At EMCD, Victoria built the localization process from scratch. The infrastructure she created now supports the product's global expansion. We sat down with Victoria to talk about what it actually takes to build an expandable localization capability at a fast-moving fintech company and why most localization problems have nothing to do with translation.