WindBorne raises $37M to make AI weather forecasting more lucrative

WindBorne Systems, a startup using long-duration weather balloons and AI-powered forecasting models, has raised $37 million in a Series B funding round to expand its commercial reach, CEO John Dean told Bitcoin World. The round, co-led by Khosla Ventures and Galvanize, with participation from TransLink Capital, Lux Capital, and existing investors, values the company at $250 million post-money.

How AI is transforming weather forecasting

The same deep learning techniques that power large language models have revolutionized meteorology. AI-based weather models can now run on laptops instead of supercomputers, dramatically lowering the barrier to entry for private companies. WindBorne, founded in 2019, initially focused on collecting unique weather data using its low-cost, high-endurance balloons. The advent of AI forecasting models in recent years enabled the company to build its own prediction systems—a capability previously reserved for well-funded government agencies and a few large corporations.

Today, WindBorne operates 20 launch sites worldwide and keeps roughly 600 balloons airborne at any given time. These balloons gather data in hard-to-reach areas, such as the eye of a typhoon. The company is now deploying aerial sensor packages that can fall into the ocean and continue measuring conditions as floating buoys. This proprietary data network, which Dean calls a “planetary nervous system,” feeds into their forecasting model, creating a significant competitive advantage.

Building a data moat and growing revenue

WindBorne’s model ingests both its proprietary data and public datasets from government weather agencies. According to Dean, adding their balloon data to forecasts improves accuracy, and the value per data point exceeds that from satellites. “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,” he said. “We’ve also been growing revenue while we’re doing that, so that de-risked the demand signal to VCs.”

The company’s primary customers are currently government agencies. The U.S. National Weather Service purchases WindBorne’s data, while the U.S. Air Force and Navy fund research partnerships, including a project to develop forecasting models that can run on ships with intermittent connectivity. The next frontier is the private sector, with initial focus on investment funds that use weather data to predict commodity prices and other business outcomes.

Why the private weather market is ready for AI

Historically, private weather companies have struggled to scale beyond government contracts. Extracting value from raw data requires specialized workflows and expertise. However, AI tools are changing this equation by making data analysis more efficient. Saloni Multani, a partner at Galvanize who co-led the round, explained: “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.”

This new funding will allow WindBorne to invest in computing resources, replace its balloon network’s satellite communications with a mesh radio system, and build out a go-to-market team to expand its private-sector customer base.

Conclusion

WindBorne Systems is positioning itself at the intersection of AI and meteorology, using proprietary data and advanced models to improve forecast accuracy. With fresh capital and a growing government client base, the company is now betting that AI can finally make weather data lucrative in the commercial world. If successful, it could unlock new applications across industries from agriculture to energy trading.

FAQs

Q1: What does WindBorne Systems do?
WindBorne uses long-duration weather balloons equipped with sensors to collect atmospheric data, which feeds into its AI-powered forecasting model to produce more accurate weather predictions.

Q2: Who are WindBorne’s main customers?
Currently, the company’s primary customers are government agencies, including the U.S. National Weather Service, the U.S. Air Force, and the U.S. Navy. It is now expanding into the private sector, starting with investment funds that use weather data for commodity price predictions.

Q3: How does AI improve weather forecasting?
AI-based models can process vast amounts of atmospheric data more efficiently than traditional supercomputer simulations, allowing for faster and more accurate forecasts that can run on standard hardware.