We target the global AI market, which has current value of €187.1B (TAM) and a CAGR of 37.3% until 2029. In this TAM, the generative AI market with €12.5B and 27% CAGR constitutes a sub-market addressed by us. AI risk management and governance sector (SAM) has a current market value of €220M and a CAGR of 42.1% until 2029. Industry leaders, e.g., Musk and Wozniak, request a stepping back from training models with an ever-increasing complexity. QuantPi’s platform is the first all-in-one, model-agnostic, plug & play solution for risk management of generative AI. For the first time, we enable companies developing or operating generative AI systems to automatically assess and mitigate major risks across dimensions such as performance, fairness, robustness, explainability, and more. Our solution assesses conformance with +100 standards and regulations, including the EU AI Act, ISO/IEC 23894, and NIST AI RMF and assists companies in their pursuit of responsible and trustworthy AI systems.

It is state of the art that multi-model ensembles (MME) of future freshwater-related hazards of climate change (CC) (e.g. derived by driving a number of global hydrological models by the output of a number of climate models) are optimal for informing CC risk management. However, studies on how to best utilize MMEs (e.g. ISIMIP MMEs) in risk management are lacking. The main project goal is to co-develop methods for providing and utilizing MME data on freshwater-related hazards for risk and adaptation assessments at various spatial scales, and to provide data in a suitable way, in order to increase availability and applicability of information for different types of end-users, with a focus on how to address uncertainties. Furthermore, future research in the framework of ISIMIP is to be co-designed, focusing on uncertainty and water. Co-development of PUNI (Providing and Utilizing eNsemble Information) methods will be done jointly by global hydrological modelers, scientists investigating co-development methods and societal information needs, boundary organizations and stakeholders (end-users). They will all participate in three stakeholder dialogues at the global scale (end-user industries), transboundary scale (Morocco, Algeria, Tunisia), and river basin scale (Ebro). PUNI methods will be co-developed by testing alternative ways of presenting MME data in support of exemplary (participatory) CC risk assessments in each stakeholder dialogue in an iterative manner, based on MME data that are either available or generated specifically in the project in response to end-user input. Expected results include a handbook on PUNI methods and a web portal at UNESCO’s International Centre for Water Resources and Global Change where end-users from around the world will be able to access hydrological MME data for their region of interest for free and in a way that suits their needs, e.g. by selecting a hazard indicator for low flows as well as its spatial and temporal aggregation.

The ECO-READY project will develop a real-time surveillance system, an Observatory offered as an e-platform and as a mobile application. This will function as the necessary singular source of information, provide real-time assessments for the food system, and update forecasts frequently and consistently. The Observatory will be available to society, policymakers, the scientific community, and the agri-food industry, and integrated with a network of 10 Living Labs, supported through the third party funding process, covering all bioclimatic regions in Europe, forming the ECO-READY project knowledge infrastructure. ECO-READY will produce knowledge-based resilience strategies, and develop tools that will be embedded on the Observatory. The underlining principle behind the ECO-READY approach is, resilient dynamism, or tackling immediate problems and long-term challenges at the same time. The Living Labs network will facilitate ‘concept to action’ through the co-creation of scenarios addressing their regional needs, the development of policy recommendations, contingency plans, and resilience strategies, and embed them on the Observatory. Furthermore, ECO-READY will develop an early warning system and decision support tools using innovative Artificial Intelligence based on holistic prediction models and Life Cycle Assessment results. ECO-READY will ensure that European farmers and society’s interests be reflected in future policy-making and monitoring, through early-stage active engagement incorporating bottom-up recommendations, facilitated by the increased usership of the digital tools developed, and resulting in increased awareness for climate-adaptive and mitigating agri-food products. Furthermore, the Observatory smart application will include tools that will empower the citizens to actively engage in policy making, and interact directly with the scientific community, farmers, and industry and policy makers, thus driving change in consumption habits.

RUBIZMO will identify business models with high potential for empowering rural communities to take advantage of the opportunities arising from improved value chain optimisation. It will directly supporting the creation of sustainable jobs and growth in rural economies, supporting a multi-actor approach for generation of shared-value. Ultimately, the project looks to contribute to rural development in Europe, supporting the Europe 2020 Strategy for Smart, Sustainable and Inclusive Growth, as well as supporting Regional and Rural Development policy. To do this, the project will identify innovative business models (developed or identified in existing projects under FP7, H2020, Interreg, Central Europe, etc.) with a significant potential to support modernisation and sustainable growth in rural economies, and relevant to the food sector, bio-based value chains and ecosystem services. Business models with the potential to contribute to the modernisation and sustainable growth of rural economies will be selected, packaged and classified according to their nature, comprising technologies, services, business support structures, financing mechanisms, etc. This will result in the creation of four practical, user-oriented tools: - Virtual library of business cases, to inspire and inform potential entrepreneurs about business opportunities; - Guidelines on creating favourable conditions for the deployment of innovative business models, to help public authorities and rural networks create adequate framework conditions for rural innovation; - Toolkit for clustering and network development in rural areas; - Transformation support tool, to help individual entrepreneurs understand which business models are best adapted to their situation, and how to go about implementing change. The project will then prepare Europe-wide upscaling and replication in rural areas using real life cases, taking account of the complexity of transferring value chains.