Case Study: Global Tech Firm improves recognition of user intent in 96 language variants with RWS

Global tech firm improves recognition of user intent in 96 language variants

A global tech firm wanted to improve its virtual assistant’s ability to recognize user intent and deliver accurate, helpful answers across 96 language variants. The challenge was to generate example user queries translated and phrased in many synonymous ways so the assistant could learn robust intent coverage and improve performance and language reach.

RWS implemented a scalable operational model (RWS Data Services for AI) providing query creation, annotation and ranking, quality control and mature operations management. Over five years RWS delivered more than 5 million queries, improved data-labeling accuracy and achieved tangible process, accuracy and efficiency gains across all 96 languages.