Few things generate as much data as simply observing Earth from above. But Ryan Abernathey and Joe Hamman very quickly realized that all that data still wasn’t enough for their startup to thrive. Their data-centric, climate tech startup, Earthmover, would need to pivot.
The pivot isn’t entirely away from climate tech, though. Instead, the company is shrinking the time scale, focusing on how climate affects daily life — in other words, the weather.
“What makes a compelling use case for our platform? Data that change frequently,” Abernathey, Earthmover’s co-founder and CEO, told TechCrunch. “That’s where there’s a lot more urgency around solutions. That [data] goes to weather, goes to fire, goes to new observations that are being generated.”
Climate outputs, he noted, are “important, but they’re kind of static,” with new data emerging every few years.
Earthmover’s core product remains its data structure, which was built to handle large, complex datasets. “In geospatial they call it a raster. In AI, they call it a tensor. In old school Fortran, they just call it an array,” Abernathey said. On top of that, the startup has built a range of tools to help customers tease insights out of their data.
