There’s a question we hear from almost every new client: “If you’re using AI, how do I know the quality won’t suffer?” It’s the right question to ask. And it deserves a straight answer — not a brochure.

Here’s exactly how we use AI, and where we don’t.

What AI actually does in our workflow

We use AI for what it genuinely excels at: speed, consistency, and volume. High-volume, repetitive content — product descriptions, UI strings, support documentation, knowledge base articles — is where AI earns its place. AI handles the first pass at scale, applying your approved terminology automatically and delivering a draft that’s already structurally close to final.

What this means in practice is that our linguists spend less time on mechanical output and more time on the content that actually requires their expertise.

Where we always keep humans in the loop

AI doesn’t replace our translators. It changes what they focus on.

There are categories of content where we always lead with human expertiseIn these areas, a wrong word doesn’t just sound off — it misrepresents your brand, alienates your audience, or creates compliance risk.

Across all content types, human review is a non-negotiable final step. AI produces the draft; a specialist reviews it. The balance between AI and human input varies by project — but human judgment is never removed from the equation.

How we train AI to sound like your brand before a human touches it

This is where a lot of agencies cut corners, and where we invest the most work upfront.

Before running a single segment through AI, we build the foundation your content needs: your glossary, your style guide, your translation memory, your approved terminology. We feed these into the workflow so that the AI output already reflects your voice and your conventions — not a generic approximation. By the time a linguist reviews the content, they’re refining, not rebuilding from scratch.

What our quality control process looks like

Not every project is suited to AI-assisted localization. The first thing we do is assess — together with the client — whether it’s the right fit, based on content type, language pairs, volume, and quality requirements. If it isn’t, we say so.

When it is, we choose the most appropriate AI-assisted approach from our toolkit and apply it. Whatever the method, one thing never changes: human review is always the final step. Our linguists check for accuracy, tone, terminology, and any AI errors before anything is delivered. Depending on the project, this final review can be handled by our team or by the client’s internal reviewers.

This human-in-the-loop commitment is formalized through our Human Approved certification, developed through our Innovation Lab — not a marketing label, but an operational framework that defines how human expertise validates AI output at every stage.

What this means for speed and cost — honestly

AI-assisted localization is faster. For the right content types, it’s more cost-effective too. But only when the setup is done properly.

The agencies that generate quality problems with AI are the ones applying it without preparation — no glossary, no brand context, no serious review process. That produces fast output that sounds wrong, and fixing it costs more than doing it right the first time. Our approach requires more investment upfront and delivers results that hold across markets and content types.

If you’re worried that AI-assisted means quality-compromised, we’d rather show you than tell you.

We use AI as a tool, not a shortcut

The goal has always been the same: content that works in every language you serve. AI helps us get there faster and at greater scale. It doesn’t change what we’re accountable for delivering.

Want to see how we integrate AI into localization workflows without compromising quality? We’ll be happy to show you our approach in detail. Contact us!