All Aboard the Localization Train: Scaling Translation of Your Confluence Docs

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Translating documentation, well, any kind of content, always faces two hurdles: accuracy and process. The consequences of getting it wrong? Sometimes it’s a funny support ticket, sometimes it’s a hefty regulatory fine. And a massive headache every single time.

So what are you options for creating AND managing multi-lingual content on Confluence?

When ‘good enough’ simply… isn’t

Rovo makes translating content in Confluence incredibly easy. If it’s not enabled, you can always lean on your favorite AI tool or Google Translate. I tested Rovo’s abilities across several languages. The verdict? It’s not bad, but it’s rough, overly literal, and occasionally misleading.

For example, Rovo translated translated the instruction to "create a Forge app" as "create an app named Forge."

While AI translations are fine for internal team sharing, they aren't reliable enough for production. General AI tools fare slightly better, but native speakers can always spot that something is "off." The wider the gap between the source and target languages, the worse the result. Bottom line – if you use AI, the burden of verifying the accuracy falls entirely on you.

From translation to internationalization

When making documentation multilingual, your goal is to give users a native experience. The text should feel as natural as if it were written by a local. It is the leap from basic translation to localization (L10n) and internationalization (I18n).

This isn't just about translating English to French. It's about nuances. You can't use the exact same financial terminology for an app in France and Quebec. Even English needs adapting: a car user manual for the UK features a boot, bonnet, and windscreen, while the US version has a trunk, hood, and windshield.

For this level of cultural and linguistic adaptation, professional translators are non-negotiable. The obvious solution would be giving them guest accounts in Confluence to clean up AI drafts. It works for a handful of pages, but it simply does not scale.

Hop onto the Localization Train

If you are scaling up to multiple products and/or regions, manual methods for maintaining multilingual content will eventually break down. Teams often struggle to plug their Confluence documentation into established localization workflows, but treating translation as an ad-hoc task is a recipe for inconsistency.

Localization is an ongoing process, and your translated content requires that it’s a part of your documentation lifecycle management. To do it properly, your workflow must handle these fundamental requirements:

• Smart Tracking: Automatically identify new or updated pages so you only translate what has actually changed.

• Bulk Operations: Export those specific changes and import the localized results in a single batch.

• Structural Integrity: Ensure every translated page perfectly mirrors the layout, macros, and formatting of the original language version.

Beyond the technical mechanics, long-term consistency requires proper linguistic assets. You and your localization vendor need to establish a glossary and build a translation memory (TM). This guarantees that your terminology never veers off track, phrases are translated identically across all your assets, and turnaround times drop dramatically.

Go pro with XLIFF

The localization industry runs on XLIFF – the gold standard for seamlessly moving content between clients and translation vendors. Out of the box, Confluence doesn’t speak XLIFF, nor does it have the native architecture to manage complex, multi-language workflows, so you need to rely on the Atlassian marketplace.

Instead of manually copying and pasting translations, you extract your Confluence pages that need translation into an industry-standard XLIFF file that your localization vendor’s tooling can process natively. Once the translation is done, you simply import the files back. The system automatically maps the translated text to the correct structure, perfectly preserving your layouts, macros, and formatting. In other words, with an translated XLIFF file, you don’t have to reconstruct the translated version of the page to match the original.

The biggest win? XLIFF-based workflows completely remove the bottleneck of scale. Whether you’re localizing 10 pages or 100, the workflow remains exactly the same: one bulk export, one bulk import. No manual updates, no broken layouts.

Personal note

I come from a linguistics background and spent years translating everything from corporate training manuals through TV show scripts to pre-flight announcements. Back then, workflow meant emailing Word documents back and forth, and the peak of technical sophistication was using a table with timestamps for translations of video transcripts.

Moving to the software industry in 2014 and adopting Confluence was a massive reality check in the best way possible. Suddenly, I was in a an environment that handled hundreds of thousands of pages in multiple languages, bound by strict compliance standards. That scale is exactly how I learned the true value of Confluence. It’s incredibly strong on its own, but you can scale it to do pretty much anything with Marketplace apps – including large-scale localization workflows.