European companies and international organizations require specialised and strategic support to successfully navigate the complexities of developing demanding Research and Innovation (R&I) projects. Rainno is an innovation consultancy based in Greece that provides expertise in collaborative R&I project management. The challenges of interoperability and data management are being tackled in many ways.
Improving information flow within the ecosystem
One of Rainno’s collaborations is with the EFRA project, an EU-funded initiative to enhance food safety and quality for European consumers. By utilizing data mining, analytics, and advanced technologies such as AI, IoT, and extreme data, EFRA addresses critical challenges related to food risks.

“EFRA’s mission is to identify and manage food risk data from various sources, feeding it into AI models to predict risks. By ensuring the effectiveness of prevention strategies and fostering trust in AI systems, the project also builds a bridge to food data innovator communities, strengthening the European food supply chains,” explains Themis Gkouthas, the project manager of Rainno.
The main challenges that stakeholders in the food industry are facing are the lack of knowledge diffusion stemming from the industry’s inherent fragmentation, and the lack of financial resources available for the deployment of advanced technologies.
“Our aim is to effectively tackle these problems by designing personalised solutions to overcome such hurdles effectively, by leveraging its elaborate ecosystem of partnerships to connect the dots between the problem and the solution. This approach boosts collaboration and knowledge diffusion, creating a virtuous cycle of innovation and sustainable growth,” says Gkouthas.
Interoperability and data integration is a challenge
One of the use cases in the EFRA project focuses on risk prediction for poultry pathogens. By employing machine learning and integrating diverse datasets, EFRA trains AI models to predict both short-term trends and long-term emerging risks in the poultry industry.
The collection and harmonization of location-based environmental data, gathered from hatchery and farm sensors, presents challenges such as data heterogeneity.
“EFRA overcomes these issues by leveraging intelligent data crawlers and advanced AI algorithms to harmonise geospatial data and adhere to strict GDPR compliance,” says Themis Gkouthas.
Organizations need support in harmonizing data formats, integrating location data with other formats, and ensuring privacy by complying to GDPR standards.
Training AI models also requires overcoming issues such as inconsistent data quality and potential biases. Gkouthas explains, that EFRA addresses these challenges by using complex algorithms to validate datasets and creating a Data Hub which collects multilingual, dispersed public data.
Furthermore, organizations need support in harmonizing data formats, integrating location data with other formats, and ensuring privacy by complying to GDPR standards. Collaborative platforms for data-sharing and enhancing the quality, richness, and usability of location-based datasets are also essential.
“Rainno enhances the exploitation as well as the dissemination/access of the Data and Analytics Marketplace, fostering an environment of participation and technology know-how transfer,” says Gkouthas.
Next steps for innovation support
Looking ahead, Rainno is committed to expanding its capabilities and supporting organizations in their innovation journey. There are new funding opportunities, such as the Horizon Europe: Widening Participation and Spreading Excellence program.
“This represents a valuable chance for enhancing research and innovation capacities. With a budget of €270 million, this initiative focuses on fostering institutional reform and increasing competitiveness within the European R&I landscape,” says Themis Gkouthas.
- Read more about Rainno’s support on Widening Participation and Spreading Excellence program.
- To learn more about Rainno’s work, visit the website rainno.eu