Intelligent Service, Resource And Data Management Platform For Optimized AI Workloads Across The Multi Provider Cognitive Computing Continuum
Overview
The 3C4AI project aims to develop an integrated, standards-driven platform for the trustworthy and efficient deployment and operation of distributed Artificial Intelligence (AI) services across the cloud-edge-HPC continuum. The project addresses the challenges of managing AI workloads across multiple providers and heterogeneous infrastructures by introducing innovative orchestration, automation and governance mechanisms.
The platform will provide a unified framework for AI workload lifecycle management, support federated multi-operator service orchestration through standardised interfaces, and enable real-time optimisation through cognitive automation. It will also facilitate distributed data orchestration through federated data catalogues and policy-compliant data sharing, while introducing capabilities such as GenAI-based intent management, hardware-aware workload placement, and decentralised trust mechanisms.
The proposed solutions will be validated through cross-domain pilots involving industrial and public-sector stakeholders, assessing performance in terms of scalability, interoperability, latency, energy efficiency and trustworthiness. By advancing secure and interoperable orchestration mechanisms for cross-operator AI services and sovereign data flows, 3C4AI directly supports the objectives of the HORIZON-CL4-2025-04-DATA-02 call.
Objectives
Provide a unified orchestration layer for multi-domain AI workload lifecycle management.
Enable federated multi-operator service orchestration via standard East–West APIs.
Deploy cognitive automation engines for real-time multi-objective optimisation.
Implement a distributed data orchestration framework with a federated data catalog and policy compliant sharing.
Offer GenAI-based intent management to translate business intents into executable service plans.
Expose a software-defined hardware abstraction layer for hardware-aware placement.
Establish decentralized trust and governance using a secure integration fabric and smart contracts.
Supply validated AI service blueprints and performance models for rapid, predictable uptake.
eBOS Role in the Project
On the technical side, eBOS leads Task T3.1 – Trusted Federation Framework and Secure Integration Fabric, which focuses on developing the security, trust and identity management mechanisms that enable secure collaboration and communication across federated domains and operators. This includes secure onboarding procedures, trust management and identity and access management capabilities.
In addition, eBOS leads WP6 – Dissemination, Communication, Exploitation and Standardisation, coordinating activities aimed at maximising the visibility, impact and uptake of project results. eBOS also leads Task T6.4 – Exploitation Activities and IPR Management, responsible for identifying exploitable assets, supporting intellectual property management, developing exploitation strategies, assessing market opportunities and promoting the long-term sustainability of project outcomes beyond the project’s duration.
Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Health and Digital Executive Agency (HADEA). Neither the European Union nor the granting authority can be held responsible for them.
