Martin Fengler knows a lot about the weather. Fengler got his PhD in mathematics, focused on numerical weather prediction, before working for Meteomedia AG, a network of weather stations in Switzerland and Germany. But while he knew a lot about weather forecasting from the prediction side, he realized the gaps that remained on the consumption side when he started working toward his pilot’s license in 2011.

“I learned a lot about weather forecasting from a user perspective,” Fengler told TechCrunch. “It’s, of course, much different than looking to the weather forecast as a mathematician and minimizing error measures. But sitting at an airstrip and you can’t fly because of fog or a bad forecast, that was quite eye opening.”

Fengler decided to launch a weather company of his own, and started Meteomatics in 2012. The St. Gallen, Switzerland-based company pulls weather data from more than 110 sources in addition to gathering data from its own autonomous weather drones. This combination of data sources allows Meteomatics to update its weather forecasts every hour and make precise predictions for areas as small as one square kilometer.

Martin Fengler
Martin FenglerImage Credits:Meteomatics

Meteomatics puts all that information into one place and built an API on top of it so its customers can use the data how they see fit, including running their own AI algorithms on top of it. Fengler, CEO, added that the fact that Meteomatics translates weather data into one uniform structure seems simple but is a feat of its own.

“It was dealing with complicated large files, data formats that are very specific to these industries, there is little standard around that,” Fengler said. “Bringing APIs to this industry was like bringing the light to the blind.”

Fengler said this focus on building a weather company aimed at enterprises, or the commercial sector in general, sets it apart from most weather companies because many are focused on one area and one audience.

“Most weather companies have a focus on the media industry and I didn’t like that,” Fengler said. “It’s very much about TV and radio, but there’s a huge demand from industry, and I was always intrigued by the topics those customers are dealing with.”

Meteomatics now works with more than 600 customers, including large enterprises like Tesla, CVS Health, and Swiss Re, among others. Fengler added that while some enterprise use cases for Meteomatics are more obvious, like a renewable energy company using weather data to predict outcomes from their wind or solar farms, others are less so, and Fengler said he learns of a new enterprise use cases for weather data almost every week.

Enterprises will likely increasingly look for this kind of data too as the impacts of climate change continue to get more intense. Climate disasters cost $150 billion a year, in the U.S. alone, with businesses shouldering a percentage of those costs.

Meteomatics just raised a $22 million Series C round led by Armira Growth with participation from Alantra’s energy transition fund, Klima, and FortyOne Group, among others. Fengler said that the company has intentionally reinvested the money it’s made back into the business over its 12-year history which has allowed the startup to avoid raising a ton of capital.

Fengler added that they usually raise a new round when they are looking to put money toward a specific project or initiative. This Series C round is no different, as the company plans to use the capital to work on its U.S. expansion by hiring a sales and marketing team focused on the region.

Some of the money from the round will also be put toward building out the company’s tech. Fengler’s grand vision is to bring precision weather, defined as down to a one-square kilometer range, to the whole globe. This level of specificity is currently available across Europe and should be available in the U.S. by the end of Q1.

“That remains the North Star for Meteomatics,” Fengler said. “It makes me get up in the morning. I strongly believe that we will be able to deliver a global one-kilometer model one day.”

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