The deep learning breakthroughs behind large language models have also paved the way for weather simulations that now run on laptops rather than supercomputers—a shift that’s reshaping meteorology. But the real challenge for AI might be simplifying how people and organizations actually put those forecasts to use. This latest funding round, co-led by Khosla Ventures and Galvanize, included additional backing from TransLink Capital, Lux Capital, and earlier investors. The investment values the company at $250 million post-funding.

WindBorne, founded in 2019, initially set out to gather a distinctive set of weather data using its low-cost sensors and long-endurance balloons. Over the past four years, advances in AI-driven forecasting models have enabled the company to generate its own predictions—something that was largely out of reach for private firms before, given the supercomputing power once required to simulate atmospheric conditions. Today, WindBorne operates 20 launch sites worldwide and keeps roughly 600 balloons airborne at any moment, collecting information from hard-to-reach places like the middle of a typhoon. The company is also starting to deploy aerial sensor packages that drop into the ocean and keep measuring as floating buoys.

This proprietary data stream, which WindBorne’s founder Dean calls a “planetary nervous system,” gives their weather model a distinct edge. The model also pulls in datasets from government weather agencies globally. “We demonstrated that when you add balloons to the forecast, you get more accurate forecasts, and the value per data point is much stronger than satellites,” Dean explained. “We’ve also been growing revenue while we’re doing that, so that de-risked the demand signal to VCs.”

Currently, WindBorne’s primary clients are government bodies. The U.S. National Weather Service buys their data, while the U.S. Air Force and Navy fund the company through research partnerships—including work on forecasting models that can run aboard ships with limited connectivity to the outside world. The next focus is commercial expansion, which for now centers on investment funds that rely on weather data to anticipate commodity prices and other market outcomes.

Beyond investing in computing power and swapping the balloon network’s satellite links for a mesh radio system, this funding will help WindBorne grow its go-to-market team to attract more private-sector clients. That’s no small feat. Over the last decade, numerous startups have tried to scale sensing ventures like earth-observing satellite networks, but many struggled to gain traction in the private sector because turning raw data into actionable insights demands experience and established workflows. Most end up selling to government agencies already accustomed to using such information.

Private weather forecasting firms do exist, but they typically earn most of their revenue by repackaging or refining government forecasts for media outlets, specialized needs like aircraft de-icing or ship routing, or for the speculators mentioned earlier. That dynamic, however, could be shifting as AI makes data analysis far more efficient. Saloni Multani, a partner at Galvanize who co-led the round, noted that the private weather market has long been constrained because “integrating weather forecasts into broader business decision-making has traditionally been expensive and difficult. We think AI changes that equation. Better forecasts make the effort worthwhile, and AI makes it much easier to connect those forecasts to the decisions businesses are trying to make.”