The focus of VIGILANCE is on reducing the effort and cost required by cybersecurity providers and Critical Infrastructure operators to establish, deploy and operate intelligent cyber-defence strategies based on Zero Trust Architecture (ZTA). The project develops an autonomous and scalable cybersecurity ecosystem capable of operating across multiple administrative domains and interconnected digital supply chains. VIGILANCE combines technologies such as Artificial Intelligence, Generative AI, adversarial AI, blockchain and quantum-secure technologies within an integrated multi-layer cybersecurity platform. The platform supports continuous verification, adaptive risk and vulnerability assessment, real-time anomaly detection, Cyber Threat Intelligence, adversarial simulation and automated cybersecurity decision support. Through an Agentic ZTA Mesh, cybersecurity capabilities are mapped to intelligent agents that can assist with threat detection, policy enforcement, security recommendations and proactive defence. The developed solutions are validated in complex multi-party and cyber-physical environments, with the overall aim of moving cybersecurity from predominantly reactive protection towards proactive, adaptive and collaborative cyber defence.

The focus of CLIMINVEST is on improving the financial sustainability and bankability of climate adaptation and resilience investments by introducing the concept of Bankability-by-Design (BbD). The project addresses major barriers that limit private investment in climate adaptation, including the lack of viable business models and clear financial returns, uncertainty associated with long-term climate investments, limited integration with investors’ ESG portfolios, difficulties in identifying and monetising adaptation and mitigation co-benefits, and the high effort required to replicate successful solutions across different regions. CLIMINVEST develops a framework that considers bankability throughout the complete lifecycle of climate adaptation projects and introduces the concepts of continuous and predictive bankability, enabling stakeholders to continuously assess investment viability and anticipate factors that may negatively affect it. The project also develops ESG risk assessment and reporting tools, techniques for replicating and localising best practices, and a multi-sided marketplace through which public authorities, climate solution providers, investors and other stakeholders can discover, assess, finance and replicate bankable climate adaptation solutions.

XR5.0 will build, demonstrate, and validate a novel Person-Centric and AI-based XR paradigm that will be tailored to the requirements and nature of I5.0 applications. The XR5.0 project aims to develop user-friendly Extended Reality (XR) applications for industrial workers using Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR). Despite improving production and safety, current XR applications often lack personalization for Industry 5.0 (I5.0). To overcome this, the project proposes person-centric XR visualizations considering individual worker traits, skills, and context, addressing challenges in technology, content, flow control, and compliance with European values. XR5.0 focuses on a pioneering XR approach tailored for I5.0, integrating it with innovative “XR-made-in-Europe” technology. This includes human-centered digital twins and advanced AI paradigms. The XR5.0 technologies will be coupled with a cloud-based XR training platform for Operator 5.0 applications, which will enable ergonomic and personalized training of industrial workers on popular processes.

HumAIne is a pioneering initiative dedicated to researching, developing, validating, and promoting a revolutionary Operating System (OS) for Human-AI collaboration. The project aims to empower AI solution integrators by creating a platform that facilitates advanced decision-making applications in dynamic and unstructured environments across various industrial sectors.

By harnessing AI to create advanced risk prediction models and encouraging healthy lifestyles, SmartCHANGE will fight back against cardiovascular and metabolic ailments all over Europe.
Objectives and Key Results:

Accurate Risk Prediction Models: Develop precise AI-driven models for forecasting the lifetime risk of non-communicable chronic diseases (NCDs) like cardiovascular and metabolic diseases among children and youth. Utilize advanced machine learning techniques, incorporating diverse variables such as behavior, fitness, and NCD biomarkers, to enhance accuracy and adaptability.

Trustworthy AI Tools: Create robust risk-prediction models and AI tools that prioritize data privacy through federated learning, data accuracy through adaptive learning, and explainability via visual analytics. These tools will offer transparent insights into predictions and risk factors, instilling user trust and understanding.

User-Centric Health Enhancement Tools and Stakeholder Engagement: Develop user-friendly tools for healthcare professionals and citizens, enabling visualization of predicted outcomes based on current and modified lifestyles. These tools will provide personalized risk-lowering strategies, empowering users to make informed decisions about their health habits. Engage health professionals, educators, children, and families in participatory design to co-create risk-prediction models, explanations, and tools, harnessing diverse insights to effectively address users’ needs.

Promoting Healthy Lives: Disseminate the SmartCHANGE project’s findings and tools, collaborating with institutions to integrate them into healthcare systems. Work towards raising awareness among healthcare professionals, families, and the broader public about the significance of healthy lifestyle choices and the potential for positive change. By providing accessible tools and actionable insights, the project aims to promote healthier lives among children and youth.

The overall aim of CODECO is to contribute to a smoother and more flexible support of services across the Edge-Cloud continuum via the creation of a novel, cognitive Edge-Cloud management framework. To achieve this aim, CODECO proposes a unique, smart, and cross-layer orchestration between the decentralised data flow, computation, and networking services, to address Edge-Cloud challenges derived from the rising Internet and IoT service decentralisation.

The AI4Gov project is aimed at exploring the possibilities of Artificial Intelligence (AI) and Big Data technologies for developing evidence-based innovations, policies, and policy recommendations to harness the public sphere, political power, and economic power for democratic purposes. The project intends to contribute to the research landscape that addresses ethical, trust, discrimination, and bias issues, and provide solutions to the challenges faced by stakeholders in modern democracies.

Modern data marketplaces are transforming how data assets are shared, traded, and utilized. Recent European initiatives have made significant strides, particularly in enhancing data monetization, regulatory compliance, and secure data exchange. However, existing centralized marketplaces face challenges that limit broader participation and accessibility. Notable limitations include complex data discovery processes, limited transparency in value-based data monetization, and insufficient integration of trusted, energy-efficient analytics. Addressing these gaps can unlock new data-driven applications in sectors like finance, retail, and smart cities, empowering innovative services that seamlessly integrate financial data. That is where FAME comes in.

FAME is on a mission to create a transformative platform and ecosystem to serve as a federated marketplace reference for the financial sector, closely aligned with the EU Data Strategy. As an EU-funded initiative, FAME combines technical, business, and legal frameworks to establish a unique, open, and publicly accessible federated data marketplace and platform for Embedded Finance (EmFi). The project adheres to emerging European data strategies, ensuring a solution that is secure, energy-efficient, and interoperable, while supporting transparent, programmable trading and pricing for data assets.

STAR is a joint effort of AI and digital manufacturing experts towards enabling the deployment of standard-based secure, safe reliable and trusted human centric AI systems in real-life manufacturing environments. STAR will research, develop, validate and make available to the AI and Industry4.0 communities novel technologies that will enable AI systems to acquire knowledge in order to take timely and safe decisions in dynamic and unpredictable environments. Moreover, the project will research and provide technologies that will enable AI systems to confront sophisticated adversaries and to remain robust against security attacks. In this way STAR’s solutions will eliminate security and safety barriers against deploying sophisticated AI systems in real-life production lines. The project’s results will be fully integrated into existing EU-wide Industry4.0 and AI initiatives (notably EFFRA and AI4EU), as a means of enabling researchers and the European industry to deploy and fully leverage advanced AI solutions in manufacturing lines.