Case Study: Tangent Works achieves real-time energy forecasting with Julia Computing

Tangent Works uses Julia to provide a comprehensive analytics solution, eliminating the barrier between prototyping and production

Tangent Works, a European machine learning company, needed a way to streamline predictive model development and remove the gap between data science prototyping and production deployment. The company’s Tangent Information Modeler (TIM) had to support advanced analytics use cases, including time series analysis, anomaly detection, and real-time energy forecasting, while keeping development fast and maintenance manageable.

Julia Computing provided Julia as the common platform for both prototyping and production, allowing Tangent Works to build TIM in parallel in Julia and C++. With Julia, Tangent Works reported much faster development, easier code maintenance, and performance on par with C++. Model-building tasks that previously took minutes in Matlab were reduced to seconds in Julia, improving productivity and making real-time analytics more feasible and cost-effective.

Tangent Works