IRIS Africa

The IRIS Africa project aims to bridge the gap in Generative AI (GenAI) adoption across Africa, focusing on empowering rural populations, women, and youth through tailored AI solutions in agriculture and healthcare. By developing context-specific Large Language Models (LLMs) and risk-classification algorithms, IRIS will enhance local capacities in addressing challenges such as food insecurity and limited healthcare access, which are exacerbated by climate change and socio-economic barriers. The project will leverage the existing EU-based LLM models MINERVA and BABELNET and adapt them to the African context through co-design with local communities, ensuring linguistic and cultural relevance. The use of these models and a risk classification algorithm will be tested through two key use cases: Continuous Glucose Monitoring (CGM) in Ghana and livestock insurance in Kenya, targeting areas with the highest need for scalable, AI-driven solutions. In collaboration with local universities, NGOs, International Research Center and SMEs, IRIS will ensure that these AI tools are not only technically sound but also accessible and trusted by the communities they aim to serve. A key objective is to foster sustainable local innovation ecosystems, including the establishment of living labs and engagement of private investors and VC to support for African start-ups, by integrating technical support mechanisms and subcontracting of local SMEs. Through these activities, IRIS will promote knowledge transfer between Africa and Europe, facilitating long-term, self-sustaining AI capabilities. The project also aims to develop policy recommendations that will support the scaling of GenAI technologies, aligning with EU and African Union frameworks for sustainable development. IRIS will contribute to the EU-Africa collaboration agenda, supporting Africa's digital transformation by ensuring that advanced AI solutions meet local needs, promote inclusion, and contribute to sustainable economic growth.