The contract resulting from this procurement procedure aims to implement innovative tools to support and strengthen the Academy’s design, development and delivery of its learning services through the implementation of generative AI, including Large Language Models, Machine Learning, Agentic Reasoning and the like
See the official notice for the place of performance.
The tenderer must have the legal and regulatory capacity to pursue the professional activity needed for performing the contract.
The tenderer, each member of the group in case of joint tender, any subcontractors (including those which do not need to be identified), and any other entities (not subcontractors) on whose capacity the tenderer relies on must ensure that are not subject to EU restrictive measures adopted under Article 29 of the Treaty on the European Union (TEU) or Article 215 of the Treaty on the Functioning of the EU (TFEU), consisting of a prohibition to make available or transfer funds or economic resources or to provide financing or financial assistance to them directly or indirectly, or of an asset freeze. The prohibition applies throughout the whole performance of the contract.
The tenderer must be in a stable financial position and must have the economic and financial capacity to perform the contract. The yearly turnover for the last 3 years must be minimum 300,000.00 EUR.
Proven expertise in Artificial Intelligence and data-driven systems, including hands-on experience with generative AI, Large Language Models, machine learning, and agent-based or adaptive reasoning systems, from conceptual design through development, training, deployment, and lifecycle management.
Demonstrated experience in learning technologies and educational innovation, especially in adult learning, non-formal education, lifelong learning, or professional training environments. This includes designing and implementing AI-enabled learning tools such as personalized learning pathways, adaptive content delivery, microlearning solutions, and intelligent tutoring or recommendation systems.
Strong background in learning platforms and simulations, with experience integrating AI into learning management systems, modelling and simulation environments, or scenario-based training tools, ideally involving dynamic, adaptive, or data-driven training scenarios.
Experience in skills analytics and workforce intelligence, including the use of AI for skills gap analysis, competency mapping, forecasting future skill needs, and supporting workforce or capability planning.
Capability to design AI-supported collaboration and community learning tools, such as AI-moderated discussion spaces, peer-learning platforms, knowledge extraction from user interactions, and social or network-based learning features.
Experience working in complex, regulated or public-sector environments, with an understanding of governance, data protection, ethics, and compliance requirements associated with deploying AI in institutional contexts.
Proven ability to integrate new AI solutions with existing systems and practices, ensuring that tools complement and enhance current learning processes rather than replacing them, and acting as a catalyst for organisational innovation.
Project Manager (PM): The tenderer shall propose a team including at minimum a Project Manager (PM). The proposed team technical capacity will be evaluated based on the criteria in Appendix TS.02 Technical Capacity checklist.
AI/ML Architect (AMA): The tenderer shall propose a team including at minimum an AI/ML Architect (AMA). The proposed team technical capacity will be evaluated based on the criteria in Appendix TS.02 Technical Capacity checklist.
Data Scientist (DS): The tenderer shall propose a team including at minimum a Data Scientist (DS). The proposed team technical capacity will be evaluated based on the criteria in Appendix TS.02 Technical Capacity checklist.
Machine Learning Engineer (MLE): The tenderer shall propose a team including at minimum a Machine Learning Engineer (MLE). The proposed team technical capacity will be evaluated based on the criteria in Appendix TS.02 Technical Capacity checklist.
Data Engineer (DE): The tenderer shall propose a team including at minimum a Data Engineer (DE). The proposed team technical capacity will be evaluated based on the criteria in Appendix TS.02 Technical Capacity checklist.
Learning Technologist (LT): The tenderer shall propose a team including at minimum a Learning Technologist (LT). The proposed team technical capacity will be evaluated based on the criteria in Appendix TS.02 Technical Capacity checklist.
Software Engineer (SE): The tenderer shall propose a team including at minimum a Software Engineer (SE). The proposed team technical capacity will be evaluated based on the criteria in Appendix TS.02 Technical Capacity checklist.
Quality Assurance Officer (QAO): The tenderer shall propose a team including at minimum a Quality Assurance Officer (QAO). The proposed team technical capacity will be evaluated based on the criteria in Appendix TS.02 Technical Capacity checklist.
Published 21 April 2026 · rebuilt nightly from the official notice.