About Engel Systems

The demand for cargo bikes, mopeds, and light electric vehicles (LEMs) for last-mile delivery and shared mobility is growing rapidly, with an average annual growth of 10%. However, large-scale deployment is hampered by high maintenance costs, frequent downtime, and a lack of maintenance infrastructure.

Engel Systems addresses this challenge with our smart IoT solution that combines vehicle diagnostics, predictive maintenance using machine learning, and integration into a network of maintenance service providers. Our platform also features advanced rider scoring capabilities that analyze driving behavior to help fleet operators reduce insurance costs by holding riders accountable for safe driving practices.

By monitoring factors like acceleration patterns, braking behavior, and route adherence across cargo bikes, mopeds, and other LEMs, our rider scoring system enables fleet operators to identify risky driving behaviors, provide targeted training, and negotiate better insurance rates based on demonstrable safety improvements. This data-driven approach to risk assessment helps operators significantly reduce their insurance premiums while promoting safer urban mobility.

Our journey began when co-founders Cesar and Marvin met during their Master's studies in Autonomous Systems in Italy. Both passionate cyclists, they initially developed ENGEL as a smart IoT device in the form of a bicycle bottle that could detect accidents and automatically send GPS location notifications to emergency contacts. This idea won "Startup of the Year" at the CLab competition.

After moving to Berlin and gaining valuable experience in the startup ecosystem, they met Aleksandra, who brought business expertise to the team. Together, they decided to pivot ENGEL with a clear focus on predictive maintenance and rider analytics for light electric vehicles. In November 2024, they joined the MotionLab Accelerator to develop their first functional prototype.