The AI-enabled AGEMERA Geo Data Exploitation and Visualization Platform has demonstrated transformative potential in the project.

To secure its long-term impact it is recommended to:

1. Establish structured dissemination campaigns targeting EU and national policymakers.
2. Build partnerships with HPC research centers to ensure scalability and cutting-edge performance.
3. Foster multidisciplinary collaborations with academia, industry, and public stakeholders.
4. Position the platform as a key enabler in European digital and green transitions, aligning with the EU Green Deal and Digital Europe Programme.

Technologies were developed with Technological Readiness Level (TRL) 5 allow the simple and seemless data analysis and characterisation at subsurface depths down to 1,000 m, with different coverage, volume, and timeframe. These technological innovations support active and agile non-invasive data collection, ahd provide highly valuable data passively with a lengthier time scale.

In this project, we conducted mineral exploration targeting, sampling, modelling, and geophysical field trialling in a total of five active mining/exploration sites in Europe and one in Zambia with total area of more then 40,000 km2 with depth up to 1000 m at some test and validation sites.

The project is working on the EIC follow up application.

The platform is re-usable and applicable in other sites/regions. The project is working on the EIC follow up application.

Mining companies require but not always possess advanced expertise to analyze, compare and validate diverse and complex data delivered by these tools. The idea to develop a full-product and ready-to-use solution based on several technologies can be facilitated by the expertise from AGEMERA partners. The AGEMERA GIS data exploitation and visualisation platform had been already used to process and visualize the data from the constituent project solutions. In the proposed project four technology providers are coming together to pioneer a new approach to data integration, based on the novel methodology of Artificial Intelligence Knowledge Packs (AIKP), under the coordination of the academic partner – the University of Oulu.