Get resilient and circular, at any time

We create digital B2B solutions for resilient and circular supply chain management. Our core product is a multi-sided collaborative platform with services for efficient supply chain management, benefiting both our customers and the environment. The platform services are enhanced using data from various sources: Copernicus Earth Observation (EO) satellite data, regional imagery and measurements related to renewable energy sources, raw materials observations and industrial dataspaces, supply chain data provided by the customers. Services are offered either as independent functional units, or delivered to customers through mobile analytics dashboards, or a digital collaborative platform. 

We work together with raw materials and manufacturing sectors, and help them convert their Green Deal policies into tangible progress.

Socio-technical challenges

Current climate discourse focuses on classical macro-economics, but neglects social dimensions, environmental consequences and inequality. Our solutions are designed to enable such innovations through climate-neutral practices and sharing economy models including sustainable supply chain  management . 

RawMatCop Academy 2023 Copernicus for Raw Materials

RawMatCop Academy 2023 was organised by the EIT Raw Materials and co-funded by the European Commission. The objectives of the introductory training from November 2023, include:

• basics of imaging technology, optical and active remote sensing in raw materials;
• applications of satellite data along the raw materials value chain, from exploration, mining and extractive activities to post-closure;
• optimised ways to monitor environmental impact and increase safety;
• practical training with Copernicus Sentinel-2 and Sentinel-1 data with following exercises:
  • mineral exploration and mapping of deposits;
  • detection of iron minerals;
  • water body detection and acid mine drainage;
  • detection of vegetation in mining areas;
  • monitoring of mining activities including waste management.

Machine Learning in Weather & Climate 

This 4 month training was organised by:

• the ECMWF (European Centre for Medium-Range Weather Forecasts), in partnership with
• the IFAB (International Foundation Big Data and Artificial Intelligence)

The objective of this training was to explore the application of Machine Learning (a branch of Artificial Intelligence) across the main stages of numerical weather and climate predictions, ranging from the acquisition and handling of input observations to their assimilation into models, and finally to forecasting and post-processing.

EUSPA Space Academy

Organised by the European Union Agency for the Space Programme (EUSPA)

  Security Awareness Programme

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