Multilingual data analysis

Multilingual data analysis combines linguistic expertise with data science to transform unstructured, language-rich data into actionable intelligence. It typically involves stages such as dataset cleaning, translation and data annotation – all designed to preserve meaning and nuance across languages.

For international organizations, analyzing multilingual data provides deep visibility into global audiences. It allows them to compare behavior across regions, monitor brand sentiment and make decisions based on insights drawn from multiple languages and cultures. RWS supports multilingual data analysis through a connected ecosystem of TrainAI and Language Weaver technologies. TrainAI prepares, cleans and enriches multilingual datasets, ensuring data accuracy and linguistic balance. Language Weaver then applies AI-powered translation and language understanding, enabling the analysis of multilingual text at scale. Together, these solutions combine intelligent automation with human linguistic expertise – ensuring insights are both technically precise and culturally informed.