A research team at the UMN has developed a system that predicts and optimizes the charge needed for commercial electric vehicles. The system is currently being applied to “last mile” delivery vehicles. The technology is a cloud-based software service that uses prior vehicle performance and external information like traffic and weather to train machine learning algorithms that, in turn, predict remaining vehicle range and battery state of charge. The result is a connected energy management system (C-EMS) that reduces range anxiety for fleet operators and enables greater penetration of electric vehicles into commercial fleets. The team, in conjunction with the UMN Venture Center, is seeking a business executive to form and launch a business with the research team and then lead and operate the business. C-VEM is already serving as the backbone to several companies providing solutions in this space.