A car accident is a crisis. Emotional stress, physical injuries, and material losses overwhelm all involved. In the developed world, a car accident is the most traumatic experience a person will ever have. MDgo aims to support drivers during this traumatic event – and improve outcomes for the over 4 million injured and 42,000 killed in car accidents annually in the U.S. alone. To change this reality, the Data Science team at MDgo is faced with many complex challenges and forced to create innovative solutions regularly. Using a few seconds of data samples from a 3D accelerometer, we manage to predict the most important outcomes of an accident: the car damage, the injuries of all occupants, if the car is driveable, and if an ambulance should be dispatched. In this talk, I’ll show our full pipeline and share a deeper insight into some of our algorithms. I’ll illustrate how without Invading the privacy of anyone involved in the accident, our algorithms predict the necessary information to help in real-time. We compiled the largest dataset in the world of real-life car accidents and crash tests to solve one of the world’s most pressing challenges.