**Problem** The range of zero-emissions vehicles (ZEV) and the initial up-front cost of ownership (ZEV) are widely cited as the most common reasons why consumers and fleet operators are not transitioning to ZEVs. In the case of battery-electric vehicles (BEV), a subset of ZEVs, original equipment manufacturers (OEMs) simply increase the number of battery cells in the vehicle in order to extend the range of the vehicle . While this boosts the range, it introduces new challenges. It first significantly increases the cost of the vehicle as battery cells are one of the most expensive components, pricing out most consumers. Secondly, it increases the CO2 emissions at the time of manufacturing, meaning the environmental benefits of a BEV are less meaningful. **Observation** A key observation is that driving style---how a driver accelerates, brakes and steers---is the single biggest factor why a BEV range by the Worldwide Harmonised Light Vehicle Test Procedure (WLTP) standard is not replicated by consumers on public roads. **What is the product & how is it disruptive** In response to this we are developing Co-pilot, the first Advanced Driver Assistance System (ADAS) that is specifically optimized for energy efficiency to extend the range of BEVs. The active ADAS solution is a Society of Automotive Engineers (SAE) Level-2 autonomous system that controls the vehicle under the supervision of the driver. Co-pilot is innovative as it leverages computer vision and artificial intelligence (AI) to understand the context of the road, the vehicle's electric powertrain, and regenerative braking systems to control the vehicle in an optimally energy efficient manner. Intuitively, Co-pilot knows when it is most appropriate for the vehicle to coast using no energy and to maximise the percentage of braking, which is regenerative, recharging the vehicle's battery. **How does the product address the problem** Co-pilot helps to solve the BEV range issue by controlling the vehicle optimally to extend the range. The device and software help to extend the range at a fraction of the price of installing additional batteries. Additionally, the extended range is achieved through a manufacturing process which has a smaller carbon footprint than alternatives.

To develop technology to improve electric vehicle journey predictions and learning algorithms and expand onto other vehicle manufacturers using machine learning.