Case Studies

Uber uses TAUS Estimate API to measure and improve the quality of its global customer care platform

The quality of content significantly influences the support experience of Uber’s customers. For instance consider an Eater who requests help canceling a severely delayed order. The same resolution, such as a refund, can be accompanied by either a robotic-sounding machine-translated message, or a message with a style and tone that expresses genuine empathy and acknowledges the user’s disappointing experience on our platform.

Quality Estimation

Speech Data

Machine Translation

NLP Services

Quality estimation

How BLEND Maximized Cost Savings with TAUS Estimate API

Quality Estimation helped BLEND confidently identify high-quality segments and remove them from the scope, dramatically reducing the cost for their clients.

Quality estimation

How Milengo Capitalized on Automation for Major Efficiency Gain

Milengo turned quality estimation into an efficiency powerhouse-driving down post-editing and unlocking new value in their translation services.

Quality estimation

Uber uses TAUS Estimate API to measure and improve the quality of its global customer care platform

Uber, a global mobility service corporation, partnered with TAUS to utilize the Estimate API as a strategic tool to enhance their customer experience.

Quality Estimation

DeMT™ Estimate API enables saving up to 76% in lead time and costs

Yamagata Europe, a leading language service provider, partnered with TAUS to streamline their translation process for a major automotive client. By implementing a customized Machine Translation Quality Estimation (MTQE) model, they achieved remarkable results, reducing post-editing (PE) efforts by up to 76% and gaining valuable insights into translation quality, saving time and costs.

Quality estimation

Unlocking Efficiency: Leveraging DeMT Estimate API to Optimize MT Workflows

MotionPoint, a global technology solutions company, partnered with TAUS to determine whether Machine Translation Quality Estimation (MTQE) models could be used to remove the human post-editing (PE) from certain machine translation (MT) workflows.

Get in touch

Have a similar challenge you'd like to address? Let's partner to customize the exact project to advance your machine learning efforts.