Pharos-CY is the AI Factory Antenna of Cyprus, established to accelerate the development and adoption of trustworthy and high-impact Artificial Intelligence (AI) solutions across Cyprus. Closely connected to the Greek AI Factory Pharos and the wider European AI Factories ecosystem, the project will provide startups, SMEs, public-sector organizations and researchers with access to advanced AI expertise, tools, AI-ready datasets and high-performance computing resources. Pharos-CY focuses on three strategic application domains for Cyprus: Health, Sustainability, and Culture & Language.
Pharos-CY will facilitate access to advanced computing resources, including the DAEDALUS High Performance Computing system in Greece, supporting organizations in developing, training, testing and scaling computationally demanding AI solutions. The project will provide modular AI services, secure data environments and domain-specific tools addressing national priorities, including digital health, energy, water, transport and climate resilience, as well as applications supporting Cyprus’ linguistic and cultural heritage.
Pharos-CY will also strengthen Cyprus’ broader AI innovation ecosystem by supporting AI skills development, knowledge transfer and responsible AI adoption. Through specialized training programmes, workshops, hackathons and collaboration with the European AI Factory ecosystem, the project will help address AI skills gaps and promote trustworthy AI practices aligned with European requirements, including the EU AI Act. Ultimately, Pharos-CY aims to expand access to advanced AI capabilities, strengthen collaboration between research, industry and the public sector, and enhance Cyprus’ position within the European AI ecosystem.
The project’s consortium consists of the Cyprus Institute (Computation-based Science and Technology Research Center – CaSToRC), all of Cyprus Centers of Excellence: KIOS, Biobank, CARE-C, CMMI, CYENS, Eratosthenes, Phaethon, the Cyprus Institute of Neurology and Genetics, the Cyprus Research and Academic Network, the University of Cyprus, and the Cyprus University of Technology. The project is coordinated by the Cyprus Institute.
Funded by the European Union. This work has received funding from the European High Performance Computing Joint Undertaking (JU) and the Deputy Ministry of Research, Innovation and Digital Policy of Cyprus, under grant agreement No 101263007. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the EuroHPC JU. Neither the European Union nor the granting authority can be held responsible for them.
