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About AIXPERT

The AIXpert Project is a large-scale, multi-institutional research initiative uniting 17 partners under the Horizon Europe Research and Innovation Programme (Grant Agreement No. 101214389) and the Swiss State Secretariat for Education, Research and Innovation (SERI).

It aims to transform how AI is developed, deployed, and trusted by society, through a comprehensive framework for explainable, transparent, and accountable artificial intelligence.

Vision

An agentic, multi-layer, GenAI-powered backbone to make AI systems explainable, accountable, and human-centered. The project envisions an adaptable and trustworthy AI ecosystem that integrates explainability, fairness, autonomy, and robustness at every stage of AI development.

Objectives

  • Build an adaptable, explainable AI-agentic platform Develop interoperable modules that connect explainability, accountability, and fairness.

  • Define and assess AI trustworthiness Establish measurable criteria and indicators for evaluating the reliability and ethical alignment of AI systems.

  • Advance explainable multimodal foundation models Drive research in interpretable vision–language–reasoning systems.

  • Demonstrate real-world impact through pilot use cases Validate the framework across sectors including healthcare, employment, and education.

Consortium Partners

The AIXPERT consortium brings together leading academic, research, and industry organizations across Europe:

Athena Research Center, University of Barcelona, Amsterdam UMC, KYKLOS, Workable, University of Groningen, Philips, Sorbonne University, CNRS, Furhat Robotics, Orfium, Novelcore, Infinity Design Labs, ITML, Barcelona Supercomputing Center, Martel Innovate, and the Vector Institute (Canada).

The Vector Institute contributes expertise in Responsible AI, bias detection, fairness benchmarking, and explainable data generation pipelines within the global AIXPERT ecosystem.

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Funding Acknowledgment

Resources used in preparing this research were provided, in part, by the Province of Ontario, the Government of Canada through CIFAR, and companies sponsoring the Vector Institute.

The AIXPERT Project has also received funding from the European Union’s Horizon Europe Research and Innovation Programme under Grant Agreement No. 101214389, and from the Swiss State Secretariat for Education, Research and Innovation (SERI).

Views and opinions expressed are those of the author(s) only and do not necessarily reflect those of the European Union or the granting authorities. Neither the European Union nor the funding agencies can be held responsible for them.