Building ResIlient Development with GEnerative AI in Education & Agriculturebroad
BRIDGE-AI · Horizon Europe grant · 2026-05-01–2029-04-30
EC contribution
Total cost
Beneficiaries
About the data
Source: CORDIS (official EU open data), Horizon Europe. Framework HORIZON · call HORIZON-CL4-2025-04 · scheme HORIZON-RIA · topic HORIZON-CL4-2025-04-HUMAN-08. CORDIS record →
Objective
BRIDGE-AI aims to improve African societies by integrating GenAI-based solutions into agricultural optimization and digital skills acquisition in rural areas of Kenya, Tunisia, and Nigeria. In addition, the project seeks to strengthen the role of women, whose participation is already significant but who remain underrepresented in certain roles.BRIDGE-AI adopts a collaborative approach between the EU and AU, through a diverse consortium made up of seven organizations: three European and four African, including SMEs, startups, universities, and research centers. The partners have prior experience in agricultural optimization projects and in learning activities.The project builds on research developed by European partners around the design of agent-based systems powered by GenAI, compatible with open standards such as NGSI-LD and widely industry-validated Open Source platforms such as the Context Broker. The main innovation of BRIDGE-AI lies in the integration of GenAI into these technological environments, with a special focus on the development of digital twins.Four case studies will be developed to improve mushroom cultivation in microclimates, maize production, pasture prediction, and pomegranate cultivation. These initiatives will address key challenges such as droughts, deficiencies in irrigation infrastructure, and the effects of climate change.BRIDGE-AI will train all stakeholders involved in GenAI. Living labs, workshops, and training programs will be promoted with the aim of strengthening the African business ecosystem.BRIDGE-AI seeks continuity beyond the project’s duration; therefore, it builds on agent-based platforms developed in previous European initiatives, adaptable to new technologies that may emerge during and after the project (a key aspect in AI today). Furthermore, the solution’s architecture is use-case agnostic, which facilitates its future application to other sectors and regions across the African continent.
Beneficiaries (8)
| Organisation | Country | Role | EC contribution | SME |
|---|---|---|---|---|
| FUNDACIO EURECAT | ES | coordinator | €400,625 | |
| UNIVERSIDAD POLITECNICA DE MADRID | ES | participant | €312,500 | |
| AUSTRIA CARD PLASTIKKARTEN UND AUSWEISSYSTEME G.M.B.H. | AT | participant | €258,750 | |
| SEAMLESS MIDDLEWARE TECHNOLOGIES SL | ES | participant | €218,125 | Yes |
| AGROINFOTECH LABS LIMITED | NG | participant | €200,000 | |
| University of Sousse | TN | participant | €197,500 | |
| JOMO KENYATTA UNIVERSITY OF AGRICULTURE AND TECHNOLOGY | KE | participant | €181,562 | |
| STE LIFEYE SARL | TN | participant | €165,000 | Yes |
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