We use a stream of your ride data and external datasets to produce real-time demand forecasts, then integrate recommendations into your operations stack. Our spatial data science platform is currently deployed in the shared mobility space for use in demand forecasting and optimization.
We are on a mission to make these services viable by bringing to bear the most powerful spatial machine learning and optimization models in existence. It is a monumental task and we know it will only be possible by assembling the best.
But what we feel separates us is that we also offer a challenge. Our work leverages the cutting edge of machine learning and optimization in service understanding how our cities move and breathe.
Every day, Zoba's software makes spatial decisions that impact hundreds of thousands of vehicles and millions of people across the world. Eventually, our work will be foundational to critical services in every city globally, from where scooters are placed to how autonomous vehicles transverse our streets.
We are a passionate team of software engineers and data scientists out of Harvard and MIT who are building the next generation of spatial analytics to improve the efficiency of cities and the lives of the people that live in them.
We are building a next-generation spatial analytics platform to power on-demand services, starting with on-demand mobility.