Localization Tips & Product Updates

When most of us think about localization, we picture someone quietly working through spreadsheets, swapping words from one language to another. Aydin Gür’s reality couldn’t be further from that image. As an Apple Retail Globalization Editor for the Turkish market, he’s reviewed and signed off on over 10 million words of customer-facing content, and his team hasn’t had a single escalation since 2018. In this episode of the Agile Localization Podcast, host Stefan Huyghe sat down with Aydin to unpack how he pulls that off, and the stories he shared were equal parts illuminating and entertaining.

When you are running dozens of localization projects, keeping track of every moving piece is hard. How do you ensure your AI engines always have enough context, your glossaries stay updated, and your published content doesn't go stale? This month, we are introducing automated guardrails to handle that operational maintenance for you. Crowdin Advisors: A background check for your project setup that automatically flags missing screenshots, thin glossaries, or unattached style guides, and many more. Re-Translation: A two-click workflow to refresh and upgrade already published AI translations whenever your pipeline improves. Crowdin Copilot in the Global UI: A personal assistant pinned directly to your top navigation bar to run complex bulk actions across your workspace via simple chat. Let's dive into the details.

When we think about shipping a product, documentation often gets treated like an afterthought, something tacked on right before the release, or worse, weeks after it. But what if the docs are the product? And what if the moment you start writing them is already too late for localization? In a recent episode of The Agile Localization Podcast, host Stefan Huyghe sat down with Rutva Safi, Senior Technical Writer at Gantner India, to explore exactly this. Rutva brings a unique lens to the conversation. With over eleven years in IT, spanning roles from developer to business analyst, quality analyst, and even law, before finding her true calling in documentation.

Multilingual websites are no longer optional. For most organizations, expanding into new markets means delivering content in multiple languages from day one. The initial focus is often on translation, getting content into new languages as quickly as possible. That approach works at first. But as content volume grows and more teams get involved, problems begin to surface. Updates fall out of sync, messaging diverges, and workflows slow down. What starts as a translation task quickly becomes a governance challenge. In this article, we explore why content governance is essential for multilingual websites, the operational challenges global teams face, and how efficient localization workflows improve multilingual content management.

We have a milestone to celebrate: the Crowdin Store has surpassed 100,000 application installations! What began as a directory of handy integration scripts has matured into a thriving, multi-category marketplace. Today, over 40 000 unique localization managers, developers, and translators, along with 3 000+ global companies, rely on the Crowdin Store to customize and automate their translation pipelines. This milestone proves one thing: there is no single 'right' way to translate anymore. Today, localization is like building with Lego. Every team simply grabs the pieces (apps) they need and builds their own perfect setup that fits their code and content. Let’s take a look at the data behind the 100,000 installs and see how high-performing teams leverage the Crowdin Store.

By Dr. Nadja Ruhl, LangOps Architect at Chainels Earlier this year, I wrote about what I called the Nordic-language trap: a specific, well-documented failure mode that happens when you use AI for pre-translation into a lower-resource Nordic language. The short version: large language models are trained on vastly more Swedish data than Danish or Norwegian data. When they're uncertain, they gravitate toward the better-resourced neighbor. The output looks plausible. The sentence structure holds. But the vocabulary is wrong. You asked for Danish or Norwegian and got Swedish instead. If you missed that article, the full write-up is on LinkedIn. The Danish case I described there was the first time I ran into this problem at scale. It was not the last.

For years, the promise of AI in localization has been shadowed by a frustrating reality: unpredictability. Traditional monolithic prompts often ignore carefully curated glossaries, hallucinate technical tags, or lose a brand’s established voice. At Crowdin, we are moving away from the take what you get approach of raw LLM outputs. Instead, we are introducing AI Pipelines – modular, multi-stage workflows that provide the guardrails and predictability needed for production-ready content.