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RENAI – RESPONSIBLE AI INFRASTRUCTURES FOR SCIENTIFIC EXCELLENCE

Objective

RenAI will drive a new paradigm in the use of Generative AI for science by delivering a suite of domain-specific and cross-domain foundation models, co-created with European research infrastructures and scientific communities. These models, trained on curated multimodal datasets—including imaging, time series, and tabular data—will support a wide range of downstream applications, from environmental monitoring to health research, while ensuring reproducibility, robustness, and scientific credibility.
The project create a federated ecosystem, aligned with EOSC federation strategy, where researchers can easily access, fine-tune, and apply these models, supported by tools for data discovery, transformation, benchmarking, and compliance. Synthetic data generation will further enhance research capacity by enabling experimentation in data-scarce or privacy-sensitive domains. To ensure usability, RenAI will provide the coResearcher, an intuitive LLM-based assistant that lowers technical barriers and enables seamless interaction with models, services, and workflows.
RenAI builds on and extends initiatives such as AI4EOSC, iMagine, and EOSC Data Commons, embedding its services into the EOSC federation to guarantee interoperability, openness, and long-term sustainability. The project also establishes strong links with EOSC governance and EU policy frameworks, aligning its outputs with the AI Act, FAIR principles, open science requirements, and security and ethics standards.
Beyond technical innovation, RenAI emphasises uptake and impact through training programmes, community engagement, and cross-disciplinary collaboration, ensuring that infrastructures and researchers alike benefit from its outputs. By integrating ethical, transparent, and trustworthy AI into scientific practice, RenAI positions Europe at the forefront of applying GenAI to accelerate discovery and address societal challenges across domains.

Fields of science (EuroSciVoc)

CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.

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Keywords

Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)

Programme(s)

Multi-annual funding programmes that define the EU’s priorities for research and innovation.

Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

HORIZON-RIA - HORIZON Research and Innovation Actions

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) HORIZON-INFRA-2025-01

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Coordinator

ATHINA-EREVNITIKO KENTRO KAINOTOMIAS STIS TECHNOLOGIES TIS PLIROFORIAS, TON EPIKOINONION KAI TIS GNOSIS
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 1 198 965,00
Address
ARTEMIDOS 6 KAI EPIDAVROU
151 25 MAROUSSI
Greece

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Region
Αττική Aττική Κεντρικός Τομέας Αθηνών
Activity type
Research Organisations
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

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Participants (22)