Case Study: MDGo achieves life-saving, real-time injury predictions with Altair Radioss simulation tools

How Simulation and Modern Software Tools can Help

MDGo, an Israeli startup, built a system to automatically alert first responders and hospitals with real‑time injury predictions after vehicle crashes. Their challenge was a lack of diverse, affordable ground‑truth data: physical crash tests are costly, slow, and limited by regulations. To generate the large, varied dataset needed to train their deep‑learning models that translate vehicle sensor data into occupant injury estimates, MDGo turned to Altair and specifically used Altair RadiossTM, supported through the Altair Startup program.

Using Altair RadiossTM crash simulations combined with real vehicle sensor feeds and Hybrid 3 dummy data, MDGo trained models that deliver EMS alerts in about eight seconds from crash to notification. The simulation approach reduced cost and time compared with physical tests (one physical test ≈ $20–30K and a month), enabled many more scenarios, and helped MDGo connect roughly 250,000 vehicles in Israel and report about 150 validated crashes to EMS to date. MDGo credits Altair’s tools, training, and support with making the scalable, life‑saving solution possible.

MDGo

Gilad Avrashi

Co-founder and CTO