Localization Workflow Automation

Most localization workflows are broken. Why are we still managing localization like it’s 2009? Developers get buried in translation files. Translators get screenshots in Slack. PMs send Excel sheets and hope for the best. The problem is that most i18n setups were never designed for fast-moving teams. I don't know about you, but I don't want another spreadsheet called “FINAL_FINAL_TRANSLATIONS_v3.xlsx”. It felt like shipping code with one hand tied behind our backs. I came across Tolgee, an open-source tool that completely changes how localization works. Instead of writing JSON files by hand or juggling outdated strings, you can translate the text right there, by clicking on it in the app or in the browser. You can check the repo here 👉 https://tolg.ee/anvzeh Some things I found compelling: • In-context translation directly in the UI • Chrome + Figma integrations for non-dev contributors • SDKs for React, Vue, Angular, Svelte, and mobile • Machine translation + translation memory baked in • Works locally, in the cloud, or self-hosted • Tolgee AI Translator: gives better translations by using screenshots and real context. It’s the first time I’ve seen localization feel like a real-time, collaborative part of the dev loop, not a separate phase that slows everything down. Curious, how do you handle localization today?

❗ Another tool for Localization Engineering! A while ago, I published an article on using batch scripting for automating tasks in localization engineering with the Okapi Framework (https://lnkd.in/dzx2-JY3) , such as prepping files for translation and quality control. Today, I’m excited to introduce you to an amazing set of tools from Maxprograms: OpenXLIFF Filters (https://lnkd.in/dbzkAqAw). OpenXLIFF Filters is an open-source and free set of Java filters for creating, merging, and validating XLIFF 1.2 and 2.0 files. Some of its standout features include: ➡ Creating XLIFF files without proprietary markup. ➡ Merging translated XLIFF files to generate translated documents. ➡ Validating XLIFF files. ➡ Generating statistics with word and segment counts, plus a graphical display of match distribution. ➡ Combining multiple XLIFF files into a larger one. ➡ Pseudo-translating XLIFF files to test conversion/merge processing. ➡ Copying the content of <source> elements to new <target> elements for all untranslated segments. ➡ Approving all segments that contain translations. ➡ Removing all <target> elements from an XLIFF file. ➡ Exporting approved segments as TMX. These tools come in the format of batch files, making their integration into larger and more complex scripts super easy and convenient for enhancing automation. My favorites are: ➡ xliffchecker.bat: Checks the validity of XLIFF files and points out any issues that need attention. ➡ analysis.bat: Generates reports from our files. ➡ pseudotranslate.bat: Performs quick and clean pseudo-translations. ➡ exporttmx.bat: Creates TMX files from approved segments in XLIFF files, ready for use in our CAT tool. If you’re into localization engineering, these tools are a game-changer! 💡

We localized WorkOS AuthKit into 90 languages in 5 weeks... every form field, tooltip, email, and API error message. LLMs made this possible. With the right setup, localization isn’t slow or painful anymore. We automated extraction, translation, and testing across the entire product. The result: users everywhere now see sign-in and sign-up flows in their own language, with consistent experience end-to-end. Full write-up by Jason Barry on how we did it (and how you can too!)

Why Smart Localization Needs Intricate Version Control, too! In my recent Agile Localization Podcast by Crowdin, I asked Julio Madrid, who organizes localization at Walmart, what lessons the language industry can learn from DevOps and CICD. 💡His response? “Treat localization like code.” That’s the mindset shift we need. If you want to improve, every string matters. Every release counts! Just like DevOps revolutionized software development, similar principles are now reshaping how we think about multilingual content: 1. Continuous Integration: Stop treating localization like a post-launch patch job. Build systems that detect new content, send it out for translation, and integrate it automatically. 2. Automation & Tooling: The less human intervention in handling files and QA workflows, the more time humans have to focus on what matters…crafting meaning and context. 3. Measuring & Feedback Loops: Track KPIs like translation throughput, quality scores, and time to market. Optimize continuously. Julio put it perfectly: “Eliminate human touch points where possible but NEVER where they add value.” By implementing Crowdin, Julio has seen teams cut project cycles by up to 75% by adopting DevOps-like approaches or as some already call it: LangOps. This isn’t just a shift in tools. It’s a shift in mindset. From chaos to coordination. From reactive to proactive. Let’s stop thinking of localization as a silo. It’s time we version strings like code, automate workflows, and measure what matters. Are you ready to DevOps your localization with LangOps?