Who we are
We believe that fighting climate change is a priority that is hampered by the lack of easy access to actionable climate data. Things are getting worse as the volume of climate model data is expanding rapidly: by 2030 there will be more climate model data than satellite data. As climate data scientists we are having fun by finding new solutions to facilitate climate data use by others.

Founder
Harilaos is an entrepreneur with scientific and business expertise in the field of weather and climate services. Previously, Harilaos founded a weather service company that was acquired by the world’s largest private weather service provider. His background is in oceanography and climatology with a PhD from University Pierre et Marie Curie and a postdoc at the University of Washington and NOAA/PMEL.

Data Engineer
Thomas is an expert in climate model
data management and post-processing.
Previously, Thomas was a research
engineer at Institut Pierre Simon Laplace where he developed algorithms and software for post processing, bias adjustment, downscaling and quality control of climate model simulations. Thomas holds a PhD in Earth Sciences and Atmosphere from University of Versailles Saint Quentin en Yvelines.

Climatologist
Dimitri is an expert in climate impacts modelling (hydrology and agronomy). Previously, Dimitri was a researcher at Institut Pierre Simon Laplace and the French National Research Institute for Sustainable Development where he implemented and used impact models for climate change impact studies in African countries. Dimitri holds a PhD in Earth Sciences and Natural ressources from Pierre Marie
Curie University.

ML Engineer
Guilhem is a machine learning engineer and Python developer trained at École Centrale de Lyon and Université Claude Bernard. He has applied deep learning and computer vision techniques to projects in industrial automation, medical imaging, and sports analytics. Skilled in Python, PyTorch, and OpenCV, he combines strong analytical skills with practical programming expertise.

ML Engineer
Fabio is a machine learning engineer with a PhD in Computer Science from the University of Bologna. His work focuses on the design and implementation of advanced neural architectures for meteorology and oceanography, including forecasting, downscaling, and extreme event detection. He has published research on diffusion models in both research and applied domains.

Enquire Now
Get in touch with our friendly professional team to discuss your climate data challenges and goals and discover how our data and services can support your activities.