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Optimising Performance and Trust for Integrity-driven Modular genAI Software Engineering

Objective

Artificial Intelligence (AI) and Generative AI (GenAI) development faces critical Software Engineering challenges (e.g. performance, modularity, automation, trustworthiness…) that hinder EU SMEs and small research groups from taking the global lead and threaten EU sovereignty. OptimAIse addresses these challenges by delivering a scalable, modular, and interoperable reference architecture that leverages European hardware to enable efficient and simplified large language model deployments. A flexible framework – aimed to deliver streamlined operations and greater productivity for developers – combines an adaptive orchestration engine (continuous performance optimisation with energy and sustainability guardrails) with tools embedding explainability, robustness and fairness as core artefacts. Besides, an end-to-end cryptographically secure traceability infrastructure ensures transparency, reproducibility, and compliance with the EU AI Act.
The OptimAIse approach will be validated in relevant environment (TRL6) over industrial use cases, showcasing specific challenges for GenAI in healthcare and robotics, also involving an AI Factory within the development and validation processes. Led by key actors in the field, a thorough evaluation using qualitative and quantitative indicators through 2 rounds of pilots will allow adjustments and refinement towards improvement, further adoption, scalation, and re-adaptation to different scenarios, opening tangible exploitation pathways.
A multi-disciplinary consortium of 7 SMEs – including a leading accelerator network – 3 research centres, 1 university, and 2 public administrations join forces, leveraging their expertise and experience in past and ongoing projects – also boosting synergies in dissemination, communication and exploitation actions – to ensure the successful achievement of the objectives, positioning Europe at the forefront of high-performance and trustworthy GenAI.

Fields of science (EuroSciVoc)

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Keywords

Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)

Programme(s)

Multi-annual funding programmes that define the EU’s priorities for research and innovation.

Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

HORIZON-RIA - HORIZON Research and Innovation Actions

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) HORIZON-CL4-2025-04

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Coordinator

TREE TECHNOLOGY SA
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 709 250,00
Address
CALLE SAN FRANCISCO, 2 PLANTA 4
33003 Oviedo
Spain

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SME

The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.

Yes
Region
Noroeste Principado de Asturias Asturias
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 709 250,00

Participants (12)

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