The SME developed and commercialized novel applications, products and services for forecasting of globally relevant, spatio-temporal problems in energy, climate, agriculture and Agri-PV. The solutions are based on original software for parallel, self-organizing modeling and high-performance computing from observed spatio-temporal data through earth observation satellites and ground measured data. By using this, the company addresses societal challenges in the intersection between satellite, earth observation data, forecasting and inductive modeling technologies.

The company developed a number of original technologies for validation of Machine Learning models implemented in commercial software products including new approaches for application domain definition and identification, cost-sensitive and ensemble modeling with per-sample prediction uncertainty, and self-organizing knowledge extraction from high-dimensional state space.

The startup company has established research co-operations with recognized scientists and experts in adaptive learning, control systems, and knowledge mining from institutions in Germany, London, Prague, Chengdu, Milan, Italy and cooperates with UNESCO.

It is currently preparing and developing a number of research and commercial projects in particular in the sectors of energy, agriculture, and climate change. Partners and investors are sought in order to complete and commercialize the product development according to different application scenarios under financial agreement or subcontracting.
Advantages and innovation
The forecasting tool is based on a core technology which enables high-resolution forecasting by means of a self-learning AI modeling. With the core technology behind, it is to be seen as pioneer by serving to different branches and scenarios.

The high-resolution forecasting system can be used for:

- Short to medium- and long-term climate forecasting includes temperatures, ozone concentration, cloud cover, aerosols, rainfall, risk assessment for insurances

- Short to medium term energy forecasting of electricity and heat load, and renewable power generation (wind, solar, selecting sites and operational planning), rainfall

- Short to medium- and long-term forecasting in Agriculture crop yields, water resources and demand, droughts, floods

More application fields are to be explored in frame of the partnership.

The SME has been awarded innovation grants from different bodies, i.e. granted by the H2020 SME Instrument, European Space Agency, national funding.

The company has a motivated team of experts complementing each other with experience in original self-organizing Machine Learning technologies and high-performance multi-core and distributed parallel computing, business, management and consulting within global corporations and international organizations, including the European Commission, the European Center for Nuclear Research (CERN) et al., and with both academic and industrial experience in the areas of renewable energies in Germany and India.

The ambition is to become a major European player in R and D driven forecasting and self-learning predictive modelling technologies, leveraging the power of earth observation data, for highly relevant industrial and societal problems.
Technical Specification or Expertise Sought
Users from energy, agriculture, Agri-PV and climate protection sectors, but also climate insurance and other branches where forecasting models play a role are addressed to participate in joint project activities.