Ex-Uber team raises $6M seed for geospatial analytics platform

Years ago, Uber had a problem. With millions of users and tens of thousands of drivers scattered across a widening expanse of the globe, the fast-growing mobility startup wanted to display more accurate maps to users about where their ride was coming from and where it was intending to go to reach its destination. The challenge is that geospatial datasets can easily reach into the petabytes, so how do you transmit and visualize such data — particularly on mobile?
“We were tasked with this massive planetary dataset,” Sina Kashuk explained about the purpose of Uber’s data visualization team, and “if money wasn’t an object, how would you architect this so that it would have the best performance?” That was the active problem that confronted a quad of engineers and data scientists tasked with solving the problem. Kashuk, Shan He, Isaac Brodsky and Ib Green collectively spent about 16 years at Uber, and they and their teammates at Uber built up what is today Uber’s extensive geospatial data visualization system. He, Brodsky and Green had joined Uber around 2014 and 2015, while Kashuk joined later in 2017.
Thankfully, the code they developed wasn’t locked inside the Uber app — core elements of their engineering were open-sourced into two libraries:, a web application that can take geospatial datasets and visualize them, and, which offers an extensible application framework for processing geospatial datasets and preparing them for visualization. According to Kashuk, Green was one of the leaders in the development of, and He developed a year later using as a base. Both libraries remain in active development on GitHub and through Uber’s Visualization team.
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