Evaluate AI across languages and markets
Native and fluent-language contributors annotate, translate, and evaluate AI output so it holds up outside its original language — not just for tone, but for accuracy and cultural fit.
Multilingual Services
Language and market coverage built into data creation and evaluation, not offered as a separate call-center service.
Multilingual Annotation
Native and fluent speakers label and classify data directly in the target language.
Translation Quality Evaluation
Reviewing whether machine or model-generated translations preserve meaning, tone, and intent.
Localized Task & Prompt Creation
Prompts and test cases written natively in-language, not translated after the fact.
Cross-Market Model Testing
Checking whether a model performs consistently for users in different regions and markets.
Professional & Technical Language Review
Checking specialized or technical terminology in-language, not just conversational fluency.
Culturally Grounded Evaluation
Reviewers who understand local context, not just literal translation of prompts and answers.
Testing Beyond a Single Language?
Tell us which languages and markets matter, and we'll match contributors accordingly.