Mirela
Augmented translation is quite a recent term, but this translation technique is becoming increasingly popular. This isn’t another machine translation pitch. It’s not meant to replace people, but to give them a better way to do the job. In this piece, we’re going to talk about what it means to augment your translation, what tools are used to make it work.
What is augmented translation?
Augmented translation is a human-in-the-loop translation approach that combines human expertise with AI-powered tools. We’re talking machine translation, translation memory, terminology management, automated quality checks, and others. All this is meant to enhance the speed, consistency, and accuracy of the translation process.
The term “augmented translation” was introduced by CSA Research in 2017. They described it as “a technology-centric approach to amplifying the capabilities of human translators.”
Unlike fully automated translation, augmented translation supports the translator by offering intelligent suggestions and automation while preserving human judgment and creativity, as well as cultural sensitivity, of course. It’s widely used in localization to scale multilingual content across different markets.
How does this help with localization?
Augmented translation can make that whole process a lot easier and a lot more scalable. It speeds things up without making a mess, because it gives translators a head start by suggesting translations from past projects (translation memory) or machine translation. You’re not starting from zero every time.
One of the biggest headaches in localization is inconsistency aka you might see the same feature translated countless different ways. But this is where augmented translation tools can solve that. They do it by enforcing preferred terms and style guides automatically.
When you’re translating hundreds of strings, it’s easy to miss a small error like a variable or a typo. Augmented translation platforms help with this too because they come with built-in quality checks that flag those issues instantly.
Many companies need to translate a lot of content, in a lot of formats, for a lot of regions. Without the right tools, that’s a nightmare. This is where augmented translation comes in again to keep things centralized, organized, and repeatable.
Tools used to augment translation
Augmentation doesn’t happen because some magical AI is doing all the work; there’s a set of technologies used to support human translators. These help them do better, faster, and more consistent work.
An important one is translation memory, which remembers past translations. If a phrase or sentence shows up again, it surfaces previous translations so the human translator doesn’t need to redo what’s already been done. Terminology management is also part of the toolkit, because it maintains approved glossaries that help enforce consistent, on-brand language across everything.
Alongside that, you have machine translation engines like Google Translate, DeepL, and others, which are great for providing quick first drafts. However, these translation suggestions aren’t blindly accepted. They’re reviewed and edited by professionals who understand context, tone, and cultural nuance.
Of course, you can’t do without a translation management platform. Tools like POEditor keep everything organized and connect teams, developers, and linguists to make sure everyone’s on the same page. When you integrate all these tools, you can work faster, get higher quality content, and launch your global content smoother.
Bottom line
Augmented translation is a major step forward for localization teams trying to meet the demands of localization. You have human linguists working with a great mix of tech to craft culturally resonant content at scale. So if you’re gearing up for your next global rollout, maybe plug in the tools that make sense for your team, fine-tune them to your brand voice, and let technology handle the heavy lifting.