Eneryield is developing state-of-the-art machine learning methods for intelligent analytics of power quality, based on several years of research at Chalmers University of Technology. The methods are capable of classifying and finding the root-cause of power quality events, which gives the necessary information to take action and mitigate disturbances, leading to reduced energy losses, reduced wear and tear of components and less stops in production. They can also model the power grid, which makes it possible to predict power quality events and variations. This is used as a control component to make power electronics react in real-time with increased efficiency.