Project Partner

In this call, PT’s contribution is to ensure that the project moves beyond a research-grade demonstration and delivers an operational, scalable foundation-model enablement stack for the energy sector—where the main challenge is not only training models, but making data sharing for training viable across multiple organisations with real constraints (confidentiality, cybersecurity, interoperability, and long-term operability).

PT will lead the engineering and operationalisation of the data-sharing backbone that allows energy actors (e.g., grid and asset operators, flexibility/DER/EV stakeholders) to contribute and consume large-scale datasets in a controlled way. This includes establishing robust data ingestion and harmonisation flows, implementing metadata and cataloguing practices that support discoverability and reuse, and enforcing access-control and auditing mechanisms so that data can be shared for model development while respecting organisational policies and legal/ethical obligations. PT will package these capabilities as reusable building blocks (connectors, APIs, governance workflows) so that the consortium’s approach remains replicable across countries and operators and stays maintainable after the project ends.

Complementing the data layer, PT will drive the production-grade AI engineering and integration pathway required to reach high TRLs. PT will set up the operational tooling and practices that make foundation-model training and deployment sustainable: dataset/version control, reproducible pipelines, model registry and lifecycle management, performance monitoring, and the integration interfaces that allow end-users to consume model outputs in realistic operational workflows. Where the consortium adopts privacy-preserving training strategies (e.g., federated approaches or controlled training environments), PT will ensure these are implemented in a way that is reliable, secure, and practical for energy organisations to run.

Finally, PT will use its broad network of potential end-users and technology stakeholders to strengthen the project’s credibility and impact from the proposal stage onward. PT will help secure early commitments from data owners and pilot followers, structure an end-user engagement mechanism (e.g., an end-user/data-provider board), and orchestrate replication activities so that project assets—datasets, governance patterns, and deployable services—translate into adoption beyond the core pilots. This “ecosystem-to-operations” role directly supports the call’s ambition to make energy foundation models feasible through trustworthy, interoperable data sharing and real-life validation.