WindBorne Systems, a weather data startup, raised a $37 million Series B round in August 2026 to scale its balloon-based data collection network and push its AI-powered forecasting tools into commercial markets, CEO John Dean told TechCrunch. The funding values the company at $250 million.
The round was co-led by Khosla Ventures and Galvanize, with additional participation from TransLink Capital, Lux Capital, and existing investors. WindBorne was founded in 2019 and is currently operating 20 launch sites worldwide with roughly 600 balloons airborne at any given time. The balloons gather atmospheric data in hard-to-reach locations, including the eye of typhoons. The company is also beginning to deploy sensor packages that drop into the ocean and continue collecting data as floating buoys.
WindBorne feeds that proprietary data into its own AI forecasting model alongside datasets from government weather agencies. Dean said balloon data has proven more valuable per data point than satellite data and produces measurably more accurate forecasts. The company’s current customers are primarily government agencies, including the U.S. National Weather Service, U.S. Air Force, and U.S. Navy. The Air Force and Navy engage WindBorne through research partnerships, including work on forecasting models that can run aboard ships with limited connectivity.
The new funding will support expansion into commercial customers, starting with investment funds that use weather data to forecast commodity prices. WindBorne also plans to spend on computing infrastructure and to replace its balloon network’s satellite communications with a mesh radio network.
Breaking into private markets has historically been difficult for sensing-focused startups. Most weather data companies generate revenue by repackaging government forecasts for niche applications such as aviation or ship routing. Galvanize partner Saloni Multani, who co-led the round, said AI may change that dynamic: “Integrating weather forecasts into broader business decision-making has traditionally been expensive and difficult. We think AI changes that equation.”
Source: TechCrunch