Noteworthy Projects

SEUD-XT

Vicomtech and LANIT are collaborating on the SEUD-XT project to raise data anonymisation standards

IZAR

In recent years, many models and algorithms have been developed for use in manufacturing, with objectives such as machine parameter configuration and production planning. However, their actual adoption in industrial settings remains limited, and they are often relegated to the role of support tools. The aim is to capture and evaluate expert knowledge and enable the factory, drawing on that knowledge, to continuously explore new hypotheses and opportunities for improvement.

EGOK-IA

The machine tool industry is producing increasingly smaller batches and customised parts, with a wide variety of materials, geometries and operating conditions. This variability introduces disturbances that affect quality, process stability and efficiency. Data-driven systems fail in the face of unforeseen situations. EGOKIA will develop technologies to detect changes, adapt autonomously and learn continuously, reduce readjustments, and improve efficiency.

IRAUBAT

IRAUBAT develops advanced solutions for the safe and sustainable recycling of lithium-ion batteries, incorporating the Safe and Sustainable by Design (SSbD) approach, life-cycle assessment and digital tools. The project will combine experimentation, modelling and simulation to optimise recycling processes, assess risks and impacts, and facilitate the efficient use of recycled materials in new batteries, contributing to a more circular and safer value chain.

6GBAIZTA

6GBAIZTA will develop Beyond-5G (B5G) solutions for critical applications in dynamic environments, focusing on low latency and determinism through 5G TSN integration, resilience achieved by combining TN and NTN networks and DECT NR+ mesh networks, and orchestration and intelligent computing with automation and AI to optimise the 5G network according to end-to-end requirements.

AURIGA

The AURIGA project aims to enhance cybersecurity in a reliable manner that complies with European regulations, using advanced AI solutions. In light of the growing digitalisation and interconnection of industries and infrastructure, it will develop technologies to ensure ongoing regulatory compliance and the comprehensive management of the cybersecurity lifecycle: detection, risks, vulnerabilities, assessments, response and recovery. All of this will be validated through proof-of-concept trials in Smart Grids.

PRISMA2

PRISMA2 desarrolla nuevos fotodetectores imprimibles, sensores fotónicos multimodales y los primeros modelos fundacionales fotónicos para industria. Estas tecnologías permitirán caracterización avanzada, control de calidad, trazabilidad y digitalización profunda en sectores como metalurgia, aeroespacial y biosanitario, fortaleciendo la autonomía tecnológica y la competitividad industrial de Euskadi.

KIDEBOT

KIDEBOT tackles the challenge of scaling up advanced robotics in the Basque manufacturing industry in the face of a shortage of skilled personnel and the inflexibility of conventional robotics. The project investigates architectures based on multimodal perception, hybrid skill learning and agents using LLM/LVLM

BIRAZ

BIRAZ aims to revolutionise industrial Virtual Worlds (VWs), transforming them from static, manually designed environments into dynamic, intelligent ecosystems capable of reasoning. By integrating Large Language Models (LLMs) and their multimodal and foundational variants, it will optimise automation in the creation of these environments and refine human-machine interaction, enabling more flexible and efficient management of industrial plants, including in Basque.

ACCURATE

SYNERGIA

SYNERGIA aims to address the limitations of current virtual training and support systems, which remain rigid, scripted and unable to respond to the cognitive, emotional and accessibility needs of diverse users.

Compliance4dpp

The overall objective of COMPLIANCE4DPP is to support the green and digital transition. It enhances the existing architecture of the sovereign and interoperable data service ecosystem through automated compliance, demonstrated in the demanding Digital Product Passport (DPP) regulation.

iLCA4ssdb

The main goal of iLCA4SSbD is to address the above challenges by developing a user-friendly Artificial Intelligence (AI)-powered integrated LCA3 (iLCA) digital platform of sustainability and safety assessment tools and datasets that seamlessly support cost-effective SSbD analysis and decision making for chemicals and materials at all stages of product development.

SENSEI

SENSEI (Societal-ready safE and transparent humaN-technology interactionS for the automatEd mobIlity ecosystem) will develop safe, inclusive and trusted Human-Technology Interaction (HTI) systems for Level 2–3 automated driving.

SYSTEMICO

SYSTEMICO will develop a systemic multisectoral multi-stakeholder approach, developing joint actions for coupling circularity and climate mitigation in industry, cities and regions, in 4 demonstration and 3 replication sites around Europe, linked to EU Mission Cities and Circular Cities and Regions Initiative (CCRI), to support the implementation of the “Climate- Neutral and Smart Cities (2025)” Mission

RemoteReadyMove

The aim of RRM is to build, validate and deploy a technological, economically viable and societal-ready RO framework, as one major pillar of the future CCAM systems complementing the ODD of AVs.

PrEVent

PrEVent offers Europe’s first comprehensive cybersecurity framework for electric vehicles, charging systems and mobility services, based on an approach aligned with the latest cybersecurity regulations, including the Cyber Resilience Act and the NIS2 Directive.

SISTEL

SISTEL uses artificial intelligence and satellite data to eliminate the impact of cloud cover on forest monitoring, enabling continuous and accurate tracking of vegetation.

IKUN

The IKUN project consortium, coordinated by Vicomtech, aims to adapt advances in Artificial Intelligence to the industrial environment, overcoming key barriers through the use of Large Multimodal Models.

CARDIAMET

Cardiovascular disease remains the leading cause of morbidity and mortality, and this project proposes an early prediction system based on NMR metabolomics and artificial intelligence. Models will be developed to identify biomarkers and discriminate at-risk populations using a large international metacohort. Finally, the models will be clinically validated and adapted to healthcare settings to improve prevention and personalized treatment.