AI-driven innovation in full swing:
ITEA Call 2024 labelled projects lead the way in digital transformation
This year, 26 strong projects have been labelled in ITEA Call 2024, highlighting ITEA’s ongoing commitment to leveraging software innovation to tackle both societal and industrial challenges. The 2024 ITEA projects show a strong mix of emerging technologies – especially artificial intelligence – with applications across healthcare, industry, energy, mobility, safety, and cybersecurity.
A key focus this year is making AI easier to adopt and more trustworthy. Projects like AIDHealth, Excellent-AI, and MentorAI tackle barriers to AI implementation through regulatory-compliant frameworks, governance models, and knowledge transfer. Other projects, such as ATLANTIS and CLEAR, use generative AI and large multimodal models to bring more automation to complex domains such as video analysis, intelligent robotics, and human-AI collaboration. The application of synthetic data, as seen in MediSynth and SYNTHESES, supports privacy-preserving innovation in health and autonomous mobility.
Sustainability and resilience are also important topics in this Call. Projects like Enginuity, ORCHESTRA, and Smart-Charge are helping to build greener engineering and energy systems. Meanwhile, safety and security remain essential themes, with projects such as CSAMGuard+, VULTURE, and SASEEBO developing innovative, new tools to protect citizens both online and in real life.
ITEA Call 2024 shows a clear and focused approach to software innovation – one that deeply integrates AI into value chains, reinforces ethical and regulatory standards, and strengthens Europe’s role in in a rapidly evolving global tech landscape.
ITEA Call 2024 labelled projects
Please find here below a summary of all the projects labelled under ITEA Call 2024.
ATLANTIS
Video-bAsed generaTive code using adversariaL AgeNts To buIld Software robots. Robots making Robots.
Project leader
Pareto AI
(Slovenia)
ATLANTIS, robots making robots, aims to automate the generation of RPA robot code from video recordings and business process information. By integrating agents based on Generative AI models, the project interprets the input, breaks it into events, generates the automation system, and evaluates it iteratively optimised using adversarial agent techniques. It seeks to improve the development and deployment lifecycle of intelligent automation solutions, reducing costs, time-to-market, and dependence on business users. ATLANTIS aims to boost productivity, traceability, and energy efficiency, enhancing the value of services like BPO, industrial automation, process monitoring.
CLEAR
Comprehensive Learning for Enhanced AI Responsiveness
Project leader
Alstom Transportation
(Sweden)
CLEAR addresses challenges in integrating diverse, multimodal data into industrial AI systems and improving the reliability of their outputs. By leveraging advanced AI techniques and context-aware capabilities, CLEAR will boost the capabilities of LMMs and LLMs to efficiently manage complex data inputs, while minimising AI hallucinations. The project intends to lower operational costs, improve safety, and boost system reliability across sectors like transportation, agriculture, and manufacturing. Additionally, it aspires to deploy AI solutions that facilitate rapid, reliable decision-making, resulting in cost savings, higher availability, enhanced user satisfaction and supporting Europe’s position in digital manufacturing and Industry 4.0.
CSAMGuard+
AI-Driven Enhancement of Online Safety: Protecting Children by Disrupting CSAM Links
Project leader
Centre for Factories of the Future Ltd
(United Kingdom)
CSAMGuard+ is an AI-powered project that aims to improve child online safety by detecting and preventing Child Sexual Abuse Material (CSAM) across digital environments. The project is driven by the rise of CSAM on social media, messaging apps, and cloud storage, and the shortcomings of traditional detection in private or encrypted spaces. CSAMGuard+ aims to deliver a privacy-compliant, real-time solution using AI techniques like content and metadata analysis, sentiment analysis, and biometric image recognition. CSAMGuard+ works to ensure timely identification of CSAM while complying with global regulations and respecting user privacy, creating a safer digital environment for children.
DiSCo
Digital Assessment and Intervention for Social and Cognitive Dysfunction in Brain Disorders
Project leader
Polytechnic Institute of Porto - School of Health
(Portugal)
The DiSCo project aims to develop a digital platform for assessing and treating cognitive and social cognition dysfunctions in neurological and mental health conditions. It targets early detection of changes that may signal the onset of these disorders and predict future deterioration. The platform includes personalised cognitive games tailored to individual impairments and performance. It enables remote monitoring through internet-based assessments and supports long-term tracking. DiSCo also delivers customised training exercises, supports clinical trials, and promotes early intervention to help reduce the effects of these conditions on individuals' daily lives.
DigiStructure
Digital Infrastructure for the Manufacturing of the Future
Project leader
Robert Bosch GmbH
(Germany)
DigiStructure addresses the growing demand for scalable, vendor-neutral industrial infrastructure in sectors like automotive, electronics and energy. It drives digital transformation by addressing challenges in scalability, flexibility, and interoperability, establishing a novel digital infrastructure for the factory of the future. Key technologies such as deterministic communication, edge/cloud computing, lightweight virtualisation, and AI will be used to create smarter, more efficient manufacturing processes. These innovations will help manufacturers across Europe to meet Industry 4.0 demands, ensuring desired adaptability and competitiveness in the evolving global market, which currently has an estimated size of approximately USD 150 billion.
Drobotize
Drones and Robots for Smart Mobility
Project leader
VTT Technical Research Centre of Finland Ltd.
(Finland)
Drobotize aims to achieve fully autonomous and secure operation of mixed fleets of robots and drones (UxVs) for logistics and surveillance. It integrates Uncrewed Ground Vehicles (UGVs), Aerial Vehicles (UAVs), Surface Vehicles (USVs), and Underwater Vehicles (UUVs) for end-to-end parcel delivery and inspection tasks. The project addresses cybersecurity challenges such as manipulation, jamming, and spoofing. Its goal is to define and demonstrate secure interoperability of tasking platforms, which will allow for on-demand access to UxV fleets, providing both B2C and B2B services. AI will optimise task allocation, enhance safety, and reduce human involvement.
Enginuity
Collaborative design exploration framework
Project leader
The Manufacturing Research Centre (MTC)
(United Kingdom)
Enginuity supports the EU Green Deal by enabling engineering sectors to meet climate neutrality goals and adopt sustainable practices. It develops a three-layer software framework - tool, model, and AI - that provides automation, integration, and data-driven decision-making. This framework helps engineers design efficiently, generate valuable data, and train AI for predictive responses to engineering queries. The project addresses sustainability challenges in aerospace, construction, and automotive sectors by enabling engineers to optimise designs, processes, materials, and energy use. It supports environmental impact analysis and lifecycle assessments, helping industries meet regulatory demands and customer expectations while balancing sustainability with cost-effectiveness.
Excellent-AI
4 Pillars for AI Business Excellence
Project leader
Fraunhofer
(Germany)
Excellent-AI supports European businesses in becoming AI-first organisations by offering AI-based solutions for strategic leadership, governance, and innovation tools tailored for AI integration. It addresses challenges in aligning AI with long-term strategies and overcoming limitations of traditional innovation frameworks. The project provides dynamic portfolio management, IT and data architecture toolkits, and governance solutions to ensure ethical, compliant, and adaptive AI use. Organisations are enabled to improve AI project accuracy by 20% and response velocity by 30%. Besides, they can achieve a 30% reduction in governance fulfilment time. Excellent-AI enhances operational resilience and strengthens Europe’s position in the global AI market.
MENTORAI
Harnessing AI to Preserve Expertise and Mentor New Talent
Project leader
ASML
(The Netherlands)
To capture the invaluable experience and expertise of experienced or retiring employees, MENTORAI transforms state-of-the-art large language models to become a dynamic and interactive source of knowledge for newer staff. The project will create AI-driven, context-aware coaching tools ensuring that new employees receive personal guidance and mentorship, like what they would get from experienced colleagues. In total, 27 partners having complementary expertise will work closely together in an iterative manner to develop and validate the different tools in a real-life environment. Jointly they will investigate market access of the AI tools.
MUST
Mobility & Urban Safety Testbed
Project leader
University of Skövde
(Sweden)
MUST addresses the growing need for advanced safety systems in urban mobility, driven by vehicle automation, connectivity, and the complexities of smart cities. The project develops a testbed that enables extensive experimentation and evaluation of AI-driven safety systems. The project aims to automate the evaluation and optimisation of safety strategies, using AI-driven tools to dynamically assess risks in urban traffic conditions, particularly those involving vulnerable road users (VRUs). Test tracks will serve as key environments for experimentation and validation of various safety interventions, including driver-assist technologies to V2V (Vehicle-to-Vehicle) and V2I (Vehicle-to-Infrastructure) coordination systems.
MediSynth
Synthetic Data for Healthcare
Project leader
TNO
(The Netherlands)
MediSynth aims to address the underuse of healthcare data due to privacy concerns by developing a Multi Modal Synthetic Data Ecosystem (MM SDE). Synthetic data, generated from original data, preserves patterns without revealing sensitive information, enabling secure sharing and improving data quality. The project will propose methods to generate realistic synthetic data and create a framework for evaluating its privacy, utility, and biases, supporting regulatory compliance. Focus areas include synthetic time series, text, audio, and multimodal data. Collaboration with end users will ensure alignment with the specific needs of the healthcare domain.
OOvFPGASIC
Object oriented acceleration on virtual FPGA/GPU
Project leader
Parkyeri
(Türkiye)
The OOvFPGASIC project introduces a runtime Field-Programmable Gate Array (FPGA) virtualisation and custom chip generation platform that enables object-oriented applications to be analysed and converted into gateware for FPGA cards. It uses object-oriented transpilers and a hypervisor for partial reconfiguration, improving software efficiency and speed. Key innovations include FPGA virtualisation from object-oriented code, custom chip generation, and real-time migration between CPU, RAM, and FPGA. The platform supports digital real-time virtual twins, 6G integration, and social media analysis. Its business impact includes enhanced automative testing, better 6G algorithms, reduced energy use, and increased security, while allowing custom chip creation without deep circuit design knowledge.
ORCHESTRA
Grid Orchestration Tool-set for Proactive Energy Management
Project leader
INEA d.o.o.
(Slovenia)
ORCHESTRA addresses challenges in grid stability caused by the rapid adoption of Electric Vehicles (EVs) and variable renewable energy sources. It introduces an AI-driven grid orchestration toolset to manage local energy resources, such as EV chargers, smart devices, Battery Energy Storage Systems and Virtual Power Plants (VPPs). ORCHESTRA’s goal is to create a sustainable, intelligent energy ecosystem that maximises the use of distributed energy resources and supports the transition to renewable energy. Outcomes include the development of an AI platform for dynamic tariff response, VPPs for coordinated energy management, and enhanced grid stability, offering new revenue opportunities through flexible energy management.
Project Allegro
Allegro: Hospitality of the Future
Project leader
Operto Guest Technologies Inc.
(Canada)
Project Allegro, a cutting-edge AI solution, aims to revolutionize the global hospitality industry by addressing the growing demand for seamless and personalized experiences. Leveraging conversational and generative AI, Allegro will enhance guest communication and create relevant content, while a staff application will streamline operations and resource allocation. An operator dashboard, powered by machine learning, will provide valuable insights to optimize efficiency, guest satisfaction, and profitability, ultimately fostering a smart hospitality community. The project aims to become a key platform for hospitality providers, offering a competitive edge by delivering a tech-enhanced experience that meets the needs of today’s travelers.
RHPMS
Rainwater Harvesting prediction and management system for sustainable urban development
Project leader
Adec innovations
(United Kingdom)
The RHPMS project aims to develop a rainwater harvesting prediction and management system integrated with wastewater treatment plants and sewer systems, aligned with urban planning frameworks. The platform will use climate models and sensors to predict rainfall patterns, optimise the design and operation of rainwater harvesting systems, and improve the efficiency of wastewater management. It will also incorporate VR training capabilities to support the design, implementation, and operation of these systems. The solution will help mitigate flood risks, address water scarcity, and enhance urban resilience through better water resource management.
SASEEBO
Safe, Secure, Efficient Airport & Airline Baggage Operations
Project leader
TAV Technologies
(Türkiye)
The SASEEBO project aims to improve airline baggage operations using AI, machine learning, computer vision and IoT technologies. It introduces AI-powered damage detection at check-in to reduce false claims, distant barcode reading for better tracking, and deep learning to identify untagged baggage. Automated monitoring will detect handling violations, while eSIM-based IoT tracking will support real-time, cross-border localisation. AI will also improve threat detection in X-ray CT scans and verify baggage ownership to prevent unauthorised exchanges. The system will be tested at major airports to ensure integration, compliance, and effective performance across different environments.
SCORE
Scenario-based Collaborative Robot Evaluation
Project leader
TWT GmbH Science & Innovation
(Germany)
SCORE addresses a critical challenge in robotics: enabling efficient and safe human-robot collaboration. The project introduces an automated tool chain that not only facilitates safety and risk assessments but also allows manufacturers and integrators to test the efficiency of their setups. Using advanced simulation technologies, LLMs and scenario-based testing, the project helps improve both safety evaluations and operational performance. By significantly reducing deployment costs and accelerating collaborative integration in industries such as manufacturing, healthcare, logistics, and service, SCORE enhances both productivity and safety, enabling more widespread use of collaborative robots in real-world applications.
STRUCTURE
Predictive Maintenance and Inspection of Transportation Infrastructure via Multi-Modal Sensing AI
Project leader
Eindhoven University of Technology
(The Netherlands)
The STRUCTURE project aims to automate and improve inspection and maintenance of transport infrastructure through a hardware and software framework built on four core technological innovations. It includes a sensor suite for detecting surface and subsurface defects using various modalities. An autonomous carrier platform will transport the sensors with precision, even in complex structures. AI algorithms will analyse combined sensor data for fault detection. And ultimately, a Digital Twin as a Service (DTaaS) will integrate inspection data with 3D models, geological maps, and traffic profiles to support asset health monitoring, predictive maintenance, and decision-making.
SYNTHESES
Synthetic Dataset Generation To Enhance Autonomous Systems using Smart ITS Data
Project leader
MORAI inc.
(Republic of Korea)
The SYNTHESES project aims to enhance the testing and validation of autonomous systems by generating large-scale synthetic datasets. It addresses the challenge of capturing rare edge-case scenarios that are critical for ensuring safety and reliability, particularly in complex urban environments. The project will develop automated tools to simulate diverse, hard-to-replicate real-world conditions. Its main goal is to create a scalable framework for generating edge scenarios and datasets to validate systems across multiple operational design domains. The project focuses on automotive use cases, supporting faster and more robust deployment of autonomous mobility technologies.
SilverCompanion
AI enhancing seniors' independence and reducing care costs
Project leader
Processa Technologies OÜ
(Estonia)
SilverCompanion consortium aims to develop an AI driven companionship system with AR avatar to improve the wellbeing of elderly living alone, reduce strain on carers, health- and social- care systems. Designed as affordable, functioning on both low-tech and smart devices, the system will learn from users’ daily behaviour to offer proactive support and empathetic communication to reduce loneliness and isolation. It will connect with health- & social- care, government, and family networks by feeding relevant data and issuing alerts when needed. SilverCompanion will improve quality of life by enhancing elderly independence and adherence to care plans. For more information, please contact us at: info@silvercompanion.eu
Smart-Charge
Sustainable management and AI-Driven Resilient Technology for Charging Infrastructure
Project leader
Acd Bilgi Islem ltd.sti.
(Türkiye)
Smart-Charge aims to improve electric vehicle (EV) charging infrastructure by using Artificial Intelligence to address issues such as grid instability, inconsistent station deployment, long charging times, and limited renewable energy integration. AI will be applied to grid management, station planning, charging optimisation, and energy use to create a data-driven system that balances demand and supports sustainable transport. The project will also implement predictive analytics to monitor battery health, optimise charging cycles, and estimate battery life. This will help users make informed decisions, extend battery lifespan and improve EVs reliability overall.
SpectralHealth
Applications of Hyperspectral Imaging in Healthcare
Project leader
VTT Technical Research Centre of Finland Ltd.
(Finland)
SpectralHealth aims to develop and evaluate the use of Hyperspectral Imaging (HSI) for diagnostics and monitoring in healthcare. The project will adapt HSI technologies, create machine learning pipelines, and develop visualisation tools to support decision-making based on HSI data. It will support harmonised data formats and standardised interfaces to enable interoperable, reusable ML-solutions. The technology will be validated in five use cases: surgery, diabetes-related conditions, dermatology, surgical tool inspection, and microbiology. SpectralHealth seeks to improve clinical workflows, support early detection, and reduce healthcare costs by enhancing efficiency.
THOE
THOE - Transforming Education with Immersive Technologies, AR/VR, AI, and Blockchain
Project leader
VBT Software A.S.
(Türkiye)
THOE aims to revolutionize the educational ecosystem by developing an interactive, immersive learning platform. Leveraging innovative technologies such as AR, VR, AI and Blockchain, THOE will provide engaging learning experiences. The platform will feature interactive 4D timelines within AR/VR environments, AI-driven research assistance and secure content ownership through NFTs on a blockchain network. THOE addresses key challenges in education, including outdated infrastructure, lack of interactivity and content ownership issues. By empowering educators, developers, and content creators with Software Development Kits and no-code tools, the platform lowers the barriers to sharing immersive educational content.
VR4Health
Immersive VR Training for Healthcare Professionals
Project leader
Aequilibrium Software Inc.
(Canada)
VR4Health aims to address the limitations of traditional healthcare training by offering AI-powered, immersive virtual environments. The platform provides cost-effective and accessible training through interactive virtual patients, real-time feedback, and adaptive learning, helping healthcare professionals refine their skills in realistic, risk-free settings. It personalises training, offers real-time analytics, and supports collaborative learning. The project combines AI-driven virtual patient interactions with VR-based therapeutic applications for patient care. A consortium of healthcare institutions, universities, and tech companies ensures the development of scalable solutions to revolutionize healthcare training and promote industry adoption.
VULTURE
Vulnerability-based Smart Prevention, Defense and Mitigation using Generative AI for Cyber Security
Project leader
VisionWare - Sistemas de Informação, S.A.
(Portugal)
Vulnerability-based cybersecurity is evolving with Generative AI. Large Language Models (LLMs) can analyse vulnerabilities reported by stakeholders, which could potentially be patched and solved. However, training these models could also be used to identify and exploit “zero-day” vulnerabilities. This stresses the need for prevention, detection and mitigation of potential harmful cyber-attacks. VULTURE will harness the potential of Generative Pre-trained Transformers by creating a revolutionary cybersecurity platform, providing a unified vulnerability-software-patch and knowledge graph, semantic search in vulnerabilities databases and OWASP listings, LLM-based reasoning, pen-testing, and AI-based mitigation and “air gapping” techniques.
