AI Data Translation & Localisation

We translate and localise the data that AI companies use to train and improve their models - and post-edit raw machine-translation output (MTPE) - as a dedicated service, separate from how we use AI tools in our own translation work.

Request a Quote Talk to Us

What This Service Covers

Two related but distinct types of work, both serving AI companies and ML teams rather than the end-readers of a translated document.

AI Training Data Localisation

Translating and localising the datasets AI companies use to train and fine-tune their models - text, transcripts, prompts and annotated content - across our language network, held to the same native-speaker quality standards we apply to client-facing translation.

MTPE - Machine Translation Post-Editing

Rather than translating from scratch, our linguists review and correct raw machine-translation output - fixing meaning, fluency and terminology errors. Faster and more cost-effective than full translation, while keeping a qualified human in the loop on every segment.

Not the same as our AI-assisted translation

Our Technology & Quality page describes how we use AI engines and tools to translate documents for our regular clients.

This page is about a separate service: translating and localising data for AI companies themselves - the material their own models are trained or fine-tuned on - not using AI to translate someone else's documents.

Why This Is a Different Kind of Work

A newer field than standard document translation, with comparatively less competition
Pricing and workflows are usually structured around datasets and batches, not single documents
Often means working directly with an AI company's data or ML team rather than an end client
Quality requirements centre on consistency and annotation accuracy across very large volumes, not just fluency in any one document

Experience Working Alongside AI Systems

We have already delivered a project that sits adjacent to this space: a community health script localised and recorded as AI-generated voiceover across 9 Indian languages, using ElevenLabs. That project gave us hands-on experience fitting our translation and quality-control process around an AI-driven production pipeline, rather than a traditional document handoff.

That same approach - native-speaker quality control applied to AI-adjacent and AI-generated content, at volume - is what we bring to AI training data localisation and MTPE work.

How We Approach This Work

NDAs available on an annual or per-project basis, as with all our work
Client data is never used to train our own AI tools or any third-party model
Native-speaking linguists review every segment - automated output alone is never the final deliverable
Access to the same language network used across our standard translation services

Working on an AI Data or MTPE Project?

Tell us about your dataset, languages and timeline, and we will scope the right approach and team for it.

Request a Quote Contact Us