Through the application of artificial intelligence and deep learning, "computing at the edge" is changing how safety systems are detecting, capturing, analyzing, and applying reasoning to events. Using real-time analysis of the data from cameras and inertial sensors mounted on a vehicle, we can not only detect unsafe driving events but also analyze the chain of events that lead to unsafe situations. We can recognize driver's positive performance in addition to areas where best practices need to be reinforced. Power-efficient and powerful deep learning processors enable us to process all of this data in real time at the edge of the network. This allows us to create an accurate and comprehensive record of driving performance that fleet managers can use to create incentives for safer driving. Insurance companies can also use this information to set proper premiums customized for individual drivers and potentially adjusted dynamically to reflect the driving environment.