Prepare multilingual datasets for AI development through controlled annotation, text and voice data workflows, linguistic review, terminology governance and quality assurance.
How it works
Prepare multilingual datasets for AI development through controlled annotation, text and voice data workflows, linguistic review, terminology governance and quality assurance.
Projects are scoped by content type, target languages, audience, confidentiality, turnaround and required review. The workflow can combine technology-assisted processing with specialist human translation, terminology management and final quality assurance.
AI is a routing choice, not a quality label
Automation can accelerate suitable content, but it changes the error profile. We decide whether AI is appropriate based on confidentiality, consequence, repetitiveness, available reference material and the amount of human verification required.