Project cooperationUpdated on 9 July 2025
Trusted AI evaluation in TEEs
About
Enable trusted AI model evaluation by executing assessments entirely within Trusted Execution Environments (TEEs). Data and models remain encrypted outside TEEs, ensuring confidentiality and integrity. Blockchain integration records evaluation results immutably, providing verifiable, tamper-proof evidence of model performance and compliance.
Data providers can monetise their data and earn incentives for quality via a fair reputation or score-based system that ensures reliable, high-quality services and data in the decentralised network.
Topic
- HORIZON-CL4-2025-04-DIGITAL-EMERGING-04: Assessment methodologies for General Purpose AI capabilities and risks
Type
- Partner seeks consortium
Organisation
Similar opportunities
Project cooperation
Secure AI with Hybrid TEE and Decentralised Governance
- Partner seeks consortium
- HORIZON-CL4-2025-04-DATA-03: Software Engineering for AI and generative AI
- HORIZON-CL4-2025-04-DATA-02: Empowering AI/generative AI along the Cognitive Computing continuum
Ambre Toulemonde
Research Engineer at iExec Blockchain Tech
Lyon, France
Project cooperation
Amadeus added value in AI/data calls
- Partner seeks consortium
- HORIZON-CL4-2025-03-DATA-13: Fostering Innovative and Compliant Data Ecosystems
- HORIZON-CL4-2025-04-DIGITAL-EMERGING-04: Assessment methodologies for General Purpose AI capabilities and risks
Guillaume ROUX
Innovation funding expert at AMADEUS
Sophia Antipolis, France
Project cooperation
GPAI-DSL: A Domain Specific Assessment Language Ecosystem for General Purpose AI
- Consortium seeks partner(s)
- HORIZON-CL4-2025-04-DIGITAL-EMERGING-04: Assessment methodologies for General Purpose AI capabilities and risks
Tanja E.J. Vos
Professor of Software Engineering and Testing at Universidad Politecnica de Valencia
Valencia, Spain