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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.

This August was about giving your AI agent the whole Crowdin toolkit. The MCP Server already lets an agent access your projects, now it has the tools to work in your codebase too. Crowdin CLI 5.0 is a complete rewrite that starts in milliseconds and speaks JSON and TOON. Four new Crowdin Skills came with it, including i18n-setup, which takes an app from hardcoded strings to multilingual on its own. Copilot can now build an AI Pipeline from a plain-language description, and you can add to a request while it's still going. There are changes across the rest of the product too: a much faster Editor and file manager on large projects, the first round of accessibility improvements, a Variables tab in the Figma plugin. We also shipped an Adobe Experience Manager connector. Let's dive into the details.

When your product protects people's homes, families, and businesses, a translation error can shatter trust, violate regulations, or leave someone unable to use a device they depend on. That's the reality Olena Azanova lives every day as Localization Team Lead at Ajax Systems, Europe's largest manufacturer of security systems. In a recent episode of The Agile Localization Podcast, host Stefan Huyghe sat down with Olena to unpack what localization really looks like when the stakes are this high and the lessons she's learned scaling a multilingual team across more than 12 markets.