predict demand.

Drive Adoption.

We 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 starting with shared mobility.


The Zoba platform (4).gif

Most mobility companies leave a substantial amount of utilization—and money—on the table by placing their vehicles in the wrong places at the wrong times, or by failing to dynamically price to meet their customers’ willingness to pay.

The Zoba Platform helps mobility companies to capture more utilization and increase revenue by predicting demand—where your consumers would want your vehicles if they could have them at any location and at any time—and optimizing their fleet distribution to meet that demand.

Zoba is currently being used by leading micromobility and car share companies in the US and abroad to increase utilization, improve customer satisfaction, and speed up adoption.


Model Demand

Utilization is not the same as demand. Utilization data shows you that customers use your vehicles where you place them. Demand inference shows you where they would have used them if they had the choice. Know your customers better.


Predict Demand

By using machine learning to examine the relationship between demand and urban data, we can predict where and when you will see demand in new cities or new areas of cities you are already operating in. Understand demand before you launch.


Optimize Networks

Mathematically optimize where you place your vehicles to maximize the demand you are capturing and increase your utilization. Take the guesswork out. Rebalance and price more intelligently.


Backed by leading investors, including: