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Recent technological advancements allow businesses to turn to machine translation post-editing. According to Nimdzi's industry report, about 50% of companies post-edit their machine translations. The concept is simple: combine the speed of machine-translated text with a linguist's review. The translation industry has advanced a lot. Yet raw machine-generated output still requires a human touch to achieve professional standards. And this is where you need machine translation post-editing (MTPE).

The idea that machine translation systems can't handle translations on a decent level is challenged daily. In our time, technology serves as an assistant rather than a competitor in many spheres. The localization and translation industry is not an exception. We're talking about CAT and TMS tools, machine translation engines, automated QA checks. Over the years, this list has not only increased, but each technology has also improved. This article will focus on machine translation, market leaders, and how you can use them to pre-translate content on the Crowdin localization management platform.

Quality translations are fundamental. Translation errors can have a big impact on your product’s success. Low-quality translations can negatively impact your relationships with clients and lower your company’s reputation. In this guide, we discuss how translation quality assurance can save translation costs and improve the quality of all your translations. Jump to: How to Improve Translation Quality | Advanced QA Strategies | QA Checklist

Translation memory allows you to use existing translations from previously translated content, rather than retranslating the same segments. This technology allows the human translator to focus on non-localized strings. Save time and allocate your budget to translate unique and important content. Keep reading to learn how you can manage your TMs and get even more benefits from them.

They say you can't improve what you can't measure. A pretty obvious statement that gets trickier if applied to the translation quality control. Localization quality assurance is a complex task that includes linguistic QA, visual QA, functionality QA, and more. You can now cope with the first one easier and get more insights into the contributors' performance with the Linguistic Quality Assurance app. Read on to learn how you can configure the app for your Crowdin and Crowdin Enterprise projects and track the quality, productivity, and efficiency of translation with the industry-standard metrics.

Software translations are often full of all sorts of mistakes. If you are speaking another language besides English, you have probably rolled your eyes at a weird or out-of-place text in an app at some point. "Oh no, couldn't they have found proper translators?" you might have thought to yourself. The thing is, the app's creators probably did find the specialists. And the problem is not that they are using just machine translation results without human edits. The problem is the lack of context. Having context is important to provide accurate translations. When it comes to UI, tackling the text without one might become especially challenging. It only seems that it might be easier because often the text is quite short. But without context in translation, this shortness makes it even tougher. How do translators know whether in this particular place 'Home' refers to the main navigation menu, a user’s physical residence, or perhaps the starting point of a process? A word without a context can be anything.

The more people are translating your project, the less time it takes to receive results, no one can doubt that. But there’s no guarantee that translations made by several people will be consistent in tone of voice, wording, and terminology usage. A glossary is one of the resources that should be added to help your translators understand the key terminology and how it should be translated. In 2026, the glossary is more than just a guide for humans – it is also a major source of context for AI. Whether you're working with linguists or using Crowdin AI, a glossary ensures that everyone (human translators or machines) speaks the same brand language.

Did you know that simply great translations might not always be the same as relevant to your app translations? Accurate translations depend on many factors such as translation context, the translation team you choose, quality of the source strings, and many other things. Companies usually concentrate on the translation team and often overlook the importance of providing translation context. Which tends to result in poor quality translations or the ones that aren’t relevant to your app.