AI translation review
You translated with AI — a reasonable choice. Before it goes public or to a regulator, a human specialist verifies every sentence, corrects what is wrong, and signs off on the result.
Using AI to translate was the reasonable part
ChatGPT, DeepL and other AI tools produce translations in seconds, at almost no cost, and the output reads well. For a first draft, that is a rational choice, and we will not pretend otherwise.
The risk starts at the next step: publishing or submitting that output without anyone qualified reading it. AI translation fails in a specific, uncomfortable way — its errors are fluent. A dropped “not.” A warranty condition that got inverted. A technical term replaced by a plausible neighbor. A detail the model simply made up. Nothing looks wrong, because reading wrong is exactly what these systems are trained not to do. If no one on your team reads the target language, you are shipping text no human has ever actually checked.
AI translation review closes that gap. You bring the AI output; a specialist verifies it against your source, corrects it, and puts their name on the result.
What the review covers
- Sentence-by-sentence verification against the source — not a fluency read-through; every segment is compared to what you actually wrote
- Meaning errors — omissions, additions, inversions and hallucinated content, the signature failures of LLM translation
- Terminology — your product and industry terms corrected to the approved form, and kept consistent across the whole document
- Numbers, units and names — verified individually, because models transcribe these confidently and sometimes wrongly
- Register and market fit — the text adjusted to how your industry actually writes in that language
Reviewers are native speakers of the target language from our sector practice groups — the medical content goes to life-science linguists, the machinery manual to engineers. Every reviewed file then gets an independent second check, our standard since 2005.
Responsibility is the product
What you are really buying is not corrections — it is accountability. An AI tool cannot take responsibility for its output; a professional can. After review you receive the corrected files, a plain-language report of what was found, and sign-off from a named, qualified reviewer stating the translation is accurate and fit for purpose. That sign-off is what you show a regulator, a notified body, a court or your own quality system when someone asks who verified the translation.
One-off rescue or standing workflow
Some clients come to us once, before a critical submission. Others make review a standing step: their teams keep drafting with AI, and every release passes through human verification first, against a term base that grows with each round. Both work. Send us the source and the AI output, and you will have a fixed quote — and an honest assessment of the output quality — within 24 hours, in 30+ languages.
Frequently asked questions
The AI translation reads perfectly. Why review it?
Because fluency is exactly what AI is good at — including when the content is wrong. LLM translation errors are fluent: a dropped qualifier, an inverted condition, a plausible but incorrect technical term, or an invented detail. If you cannot read the target language, you cannot tell a great translation from a confident wrong one. A specialist can.
Is this cheaper than translating from scratch?
Usually, yes — when the AI output is reasonably good, the reviewer corrects rather than rewrites. We assess a sample first and tell you honestly which situation you are in, with a fixed quote within 24 hours either way. If retranslation would be cheaper, we say so before you spend anything.
What do we receive at the end?
Corrected files, a summary of what was found and fixed, and a sign-off: a named, qualified reviewer confirming the translation is accurate and fit for its purpose. For regulated content that gives you a documented human verification step for your records.
Can this become an ongoing workflow instead of a one-off rescue?
Yes, and that is where it works best. You keep generating drafts with your AI tools; we review before each release, working against a term base we build from your content. Over time the reviews get faster because your terminology and past corrections carry forward.