Swiss startup Jua has launched its AI-powered platform that gives the meteorological industry customized weather models, giving the sector more oversight of our increasingly unpredictable weather patterns. Jua raised €2.5 million to accelerate the launch.
As a result of climate change, our global weather patterns are increasingly unpredictable and have an encroaching impact on people’s everyday lives. From heightened flood risks to periods of drought, and from intensifying winter storms to extreme heat, weather-based events are felt the world over and it’s having an impact on societies and economies.
Aiming to advance humanity’s understanding of weather and climate, Zurich-based entrepreneurs Andreas Brenner (CEO) and Marvin Gabler (CTO) have just scored fresh funding to launch climate tech platform, Jua.
With hubs in Zurich, Berlin and Cape Town, Jua was founded in 2022 after 3 years of research and development in creating the proprietary data platform.
The startup has now raised €2.5 million in pre-seed funding. The round was led by Promus Ventures, a VC firm that invests in deep-tech and space tech companies, including Spire, Mapbox, ICEYE and Rocket Lab.
Pierre Festal, Partner at Promus Ventures: “The team at Jua have built one of the most ambitious AI applications that provides accuracy far beyond what the weather industry has to-date considered feasible. We are delighted to back them and to help support the launch of this category-defining technology.”
Participants in the round included prominent investors Siraj Khaliq (Co-Founder of the Climate Corporation & former Partner at Atomico), Mehdi Ghissassi (Head of Product at Alphabet-acquired Deepmind), and Swiss-based Session.vc (founded by seasoned entrepreneurs and first check investors of companies like On Running, Bexio or Nutmeg). Promus Ventures Partner Pierre Festal is also joining the Jua board.
The platform is currently being offered to a select number of customers, on request, and is set to be released to a wider audience in early 2023.
AI-driven weather modelling
According to a recent global survey by the World Economic Forum, over half of the adults in the world say that climate change has had a severe impact on their lives, and a third are worried they might be forced from their homes. These worldwide weather-based events, such as the severe flooding in Pakistan or the recent extreme heat wave across Europe, will impact businesses and societies in both the short term and the long term – and we need to be better prepared to deal with these challenges.
Until now, there have been limited tools that enable a full understanding of the interplay between weather patterns and natural disasters, in an accurate data-driven way. That’s what Jua has set out to achieve.
Andreas Brenner, Co-founder and CEO of Jua, explained: “We are going to change perceptions of weather prediction forever. In terms of geospatial resolution, temporal resolution and update frequency, our first model already outperforms all existing numerical models by several orders of magnitude. We now enable everyone from small startups to large companies to get access to much better weather data than they have ever seen before.”
The Zurich-headquartered team provides startups, companies, government institutions and researchers the ability to create purpose-built weather models in a matter of hours. The new platform contains one of the largest weather and geospatial data sets available and includes a training infrastructure that enables even non-technical users to customize their models with proprietary data.
The weather prediction model provides a global one-kilometre square’s worth of coverage for every five minutes and can predict more than fifteen different weather-based parameters, including precipitation, air pressure, wind speed and wind direction. Some regions are covered in up to two hundred and fifty meters squared resolution, and the model is updated every fifteen minutes, enabling significant improvements in forecasting extreme events.
The result is a tool that provides up to 25-times higher spatial resolution and ten-times higher temporal resolution than conventional alternatives. This massive resolution increase is achieved via an end-to-end deep learning approach and tens of millions of sensors, in comparison to the hundreds of thousands of sensors used by current standard models. An additional benefit of the new deep learning-powered model is its energy efficiency, with it requiring over a thousand times less computing power than any other numerical weather model.
Marvin Gabler, Co-Founder and CTO, added: “It is important to understand that we took the risk of completely rethinking the technical approach to weather forecasting and built a new technology from the ground up. Besides accuracy, our approach also brings completely new capabilities to the market. To the energy sector, it brings the first probabilistic short-term forecast which can significantly improve their profitability. We won’t stop here. This is our first platform to be released and we can’t wait to announce all the things we are working on over the coming months and years.”