Reformulate

BAT is an autonomous data-driven forecasting platform for energy and utilities. This platform provides utility companies with machine-learning models that improve energy distribution and usage efficiency. It also increases the efficiency of the power generation equipment by quickly discovering and addressing underperforming elements. Our machine-learning models prevent failures before they occur thus increasing uptime and reducing maintenance time and costs. BAT operates as a decision support system that gives insights to a human operator, who makes the final decisions. In parallel with the forecasting and modeling process, BAT keeps track of the actual procurement of the energy on the market and the algorithm-suggested value. The platform simultaneously helps and learns from the operators about the optimal way of dealing with maintenance issues. This is implemented by utilizing an autonomous machine learning pipeline processing multiple models tailored to the energy and utility industries. BAT helps the energy and utility industries to: reduce the time and effort in modeling and forecasting energy consumption and production, optimize over integrated supply-demand model, transfer knowledge from operators to the decision support system, reduce operation costs, and increase their capacity for further innovation and investments.