Unlock global users with data for the world.
We specialize in human data solutions that are multilingual, providing expert-validated data for global models. Our DATAtalent network has over 300k AI contributors, linguists, and domain experts who can work in over 200 languages including rare and low resource languages.
Collect text, audio, images and video across languages, cultures and regions to train AI for global use. Including collection for physical AI. For robotic training, household devices across countries.
Turn multilingual data into reliable training datasets with human annotation that captures meaning, context, and cultural nuance.
Evaluate AI performance, safety and cultural relevance across languages with native speakers and domain experts.
Access a global network of vetted AI contributors and domain experts spanning 200+ languages through our DATAtalent network.
“A robot learning to load a dishwasher, hand someone a glass or navigate a hallway is not necessarily learning a universal skill. It is learning a culturally and geographically specific version of that skill. Physical AI is not culturally neutral.” Véronique Özkaya, CEO, DATAmundi, Robots Don’t Have a Culture Problem: Their Training Data Does, Forbes Technology Council, October 2026
Train and evaluate LLMs to understand and generate directly in the target language, capturing native meaning and nuance beyond translation from English.
Build multilingual AI for healthcare, legal, financial, and STEM applications with human experts who create, review and evaluate data for domain accuracy and local cultural context.
Test safety and alignment in every language your AI supports. Native speakers and domain experts assess harmful outputs, cultural bias and local risks that English-only testing can miss.
Supported by AIDA Hub, our data operations platform, we manage multilingual data workflows across the entire AI data lifecycle. Including global collection, annotation, transcription (AI with human-review) and quality validation across all data types and modalities.
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