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“Dribia’s expertise enabled us to exploit the full potential of our data and allowed us to become a data-driven company from the very start. They quickly understood our poblems and needs, and build a powerful and solid algorithm, capable of scaling to many cities.”


Intense use of public data sources and APP data usage to predict shared-mobility demand.


Fast deployment and enhancement of start-up data analytics capabilities.


Scalable solution that can be deployed in a new city in a few hours.


Shared micro-mobility services are key players in a modern network of sustainable means of urban transportation. Citizens benefit greatly from a comfortable and flexible experience, but operators face new challenges regarding logistics and maintenance. How do we manage rapidly changing needs and maximize user engagement while limiting costs and resources?


For Reby, a start-up that manages a fleet of shared electric kick scooters, we created an algorithm that computes how the demand is distributed in the city. We use open data from the city and private usage data to predict when and where a kick scooter will be needed. This allows us to design a relocation strategy that maximizes fleet performance and optimize distribution routes.