WindBorne Systems Wins US Air Force Contract Worth Up to $49 Million for Balloon Data

Air Force Contract

The U.S. Air Force will buy data collected by WindBorne Systems' fleet of autonomous weather balloons under a new contract that could be worth nearly $50 million to the startup. The deal, worth up to $49 million, is the single-largest contract the company has participated in.

WindBorne currently has about 700 weather balloons flying around the globe, collecting atmospheric sensor readings that the company sells to customers and also feeds into its own AI weather forecasting model. The Air Force pays only as it needs data and can place orders for specific regions at specific times. So far, it has ordered $1.7 million worth, and executives expect more orders to follow.

The contract was awarded without competitive bidding. WindBorne co-founder and CTO Andrey Sushko told TechCrunch that the deal represents a determination by the government that, for the capability of collecting global data, the company was the only one able to provide it in a way that met operational needs. He said the contract is largely a vehicle through which continued growth of the constellation can be supported, along with research and development to improve the hardware and performance of the balloons.

AI Weather Forecasting

WindBorne, founded in 2015 and based in Redwood City, California, is one of the first organizations to directly feed empirical data into a deep-learning weather model. The company has worked closely with the U.S. government, particularly the National Weather Service and the U.S. Air Force and Navy.

Earlier this summer, the company released the latest version of its forecasting model, WeatherMesh 6, which it says provides more accurate forecasts than the traditional model run by the European Centre for Medium-Range Weather Forecasts, which simulates the atmosphere using the laws of physics. CEO John Dean said in August that the company had raised a $37 million Series B round to continue scaling its business.

Since the arrival of transformer model architectures and the ECMWF's release of a massive weather dataset a few years ago, AI weather forecasting has become one of the more productive uses of deep-learning technology. Meteorologists previously relied on expensive supercomputers running detailed equations that approximate how the atmosphere behaves. Now, end-to-end learning can ingest decades of weather data and issue predictions more quickly. Models built by frontier labs and government agencies are proving more accurate than traditional forecasts, although both types of forecasts are still required to enable useful understanding of the weather.

Typhoon Data Collection

In August, WindBorne became the first organization to send an unpowered flight system, one with no engine, to collect data in the eye of a typhoon. The company maneuvers its balloons by adjusting their altitude, bleeding air, or dropping sand carried as ballast, to send the vehicles into winds that take them where they need to go.

Sushko called it a pretty novel step, requiring two ingredients: good wind and weather models and knowing how to navigate them, and a large enough constellation that balloons are in the right places. He said it is one of the first times that a deep-learning model was used for actual operational decisions.

Sources: Techcrunch