Post-editing and QA of AI-translated documents and AI-localized software

Post-editing and QA of AI-translated materials is a fairly new service on the market.

As your Expert-in-the-Loop (EITL), I apply years of domain expertise to thoroughly review, correct and refine your AI-translated content, so your documents are fit for publication and your software is fit for release.

Without human oversight, AI-generated translations can introduce errors that damage your brand reputation, mislead customers, and even expose your business to legal liability - particularly in regulated sectors like ICT, e-commerce, and SaaS. The EU AI Act establishes a framework in which human oversight of AI-generated content is a key principle, especially in client-facing and regulated contexts. Unreviewed machine output is a hidden risk to your revenue and your customers' trust. An EITL ensures your translations are accurate, on-brand, and audit-ready.

What does post-editing of AI-translated documents and AI-localized software entail?

Fixing AI-related issues

  • Fixing hallucinations (inaccurate or nonsensical outputs)

  • Translating parts where AI translated into the wrong language or failed to translate part of the text (language contamination)

  • Fixing parts where AI added or omitted content (source detachment)

  • Checking for other known strange AI behaviour, e.g. the replacement of country codes in telephone numbers

  • Making terminology consistent (AI favors interchangeable terms, which can lead to confusion)

  • Replacing AI-translated parts by the correct versions when the text refers to existing translations, e.g. titles of existing documents, EU legislation, strings in apps

Fixing mistranslations

  • Correcting mistranslations caused by misinterpretations

  • Correcting mistranslations caused by lack of context

Enforcing brand consistency

  • Making sure the client’s preferred terminology is used

  • Making sure the text is consistent with the client’s brand voice and the client’s style guide is followed

Fixing linguistic issues

  • Fixing grammatical issues, e.g. the use of incorrect pronouns when referring to a noun that is not in the same sentence

  • Fixing punctuation issues, e.g. when the source punctuation is copied instead of using the target language’s punctuation rules

  • Rewriting overly literal and unnatural sounding translations

  • Fixing other linguistic issues

  • Checking readability

Fixing localization issues

  • Making sure all localization of dates, times, currencies etc. is correct

  • Checking cultural sensitivities

  • Adapting examples and stories to local situations and circumstances

  • Making sure if the locale is suitable (e.g. if it is suitable for use in both The Netherlands and Belgium)

Checking software-related requirements

  • Fixing issues with length restrictions

  • Fixing layout issues

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