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Swedish startup Tempivo AI is piloting a wireless sensor solution that continuously monitors water temperatures in municipal buildings — replacing manual spot checks with real-time data and automated compliance documentation. Tested at RISE Research Institutes of Sweden in Kista as part of the CitCom TEF programme, the system uses AI to detect Legionella risk as it develops, rather than after the fact. For property managers overseeing schools, care homes, and hospitals, it offers a practical path to safer water and simpler regulatory compliance.

From Barcelona to Copenhagen, CitCom.ai made its mark at major European events in 2025 — championing trustworthy AI adoption for smart cities and communities. Across conferences, workshops, and matchmaking sessions, the initiative advanced its mission to help cities scale AI responsibly, strengthen data infrastructure, and build cross-border collaboration. Here’s a look back at the key moments that defined CitCom.ai’s most successful year yet.

The City of Luxembourg partnered with the Luxembourg Institute of Science and Technology (LIST) to independently assess a multilingual citizen-facing chatbot before any large-scale deployment. Through LIST’s AI Assessment Sandbox, the chatbot was tested for bias and fairness across multiple languages — revealing discrimination patterns that were subsequently addressed. The case illustrates how cities can take an assessment-first approach to AI adoption, building resident trust without slowing down innovation.

CitCom.ai continues to consolidate its position as a leading European TEF for urban AI, expanding its experimentation pipeline, strengthening industry engagement, and accelerating the deployment of market-ready solutions. The latest indicator update reflects steady growth across all operational dimensions.

In a CitCom.ai experiment in Mechelen, the city and Telraam explored whether data from their low-cost multimodal sensors can reveal patterns linked to cyclist risk. Early results are promising and suggest such data could help cities move from reactive to proactive traffic safety measures.

The French CitCom.ai Node, led by LNE, helps you develop, test, and validate safe, reliable and ethical autonomous mobility solutions. By combining decades of testing expertise with advanced AI evaluation, it gives you direct access to high-value facilities and tailored experimentation environments.

Our first edition is packed with real-world stories of AI being tested and deployed in European cities. Discover how AI-powered cameras are reshaping urban data privacy, how digital twins are driving climate neutrality, and get highlights from our recent events.

Imec researchers presented findings at Belgian AI Week in March showing that transfer learning can enable smaller, data-poor cities to achieve accurate traffic predictions without large sensor networks. By adapting AI models trained in data-rich cities, even cities with limited local data can outperform models built from scratch, bringing scalable, inclusive AI within reach for urban mobility.

Cities that have already prioritised and budgeted for green transition are now becoming a stronger driving force for AI-demand within CitComTEF’s network of cutting-edge solution providers.

In 2024, the City of Mechelen explored a new way to improve cycling safety through the CitCom.ai project. Instead of buying a ready-made solution, the city launched an innovative procurement process that allowed multiple companies to test emerging, data-driven ideas in a real urban setting—showing how procurement itself can drive learning and innovation.

In CitCom, the interaction between companies, cities, and other public institutions is crucial. They can all bring different perspectives. The role of cities is largely to focus on the challenges that society faces and in this way contribute to qualifying technological development.

The latest customer satisfaction survey paints a very positive picture of CitCom.ai and confirms the growing value of the TEF for SMEs, startups, public-sector organisations, and academia.

The company Gimic develops AI-based systems for automated quality control in the manufacturing industry and is the first to undergo RISE’s new Risk Assessment Analysis Service for evaluating systems in relation to the EU AI Act. The service has been developed within the framework of CitCom.ai TEF.

CitCom.ai TEF had a highly productive and inspiring presence at the Smart City Expo World Congress (SCEWC25), the world’s leading event for urban innovation.

Imagine your city’s traffic cameras doing more than just monitoring. They could be earning money by providing valuable data to researchers and businesses, while protecting citizens’ privacy. A use case together with companies Felicity Smart Infrastructure, Milestone Systems, KMD, Aalborg University and CitCom.ai test sites UPV, LIST and DOLL is making that a reality, showing how AI cameras can safely and efficiently share information, opening new possibilities for everyone.

The LiDAR test was carried out to see whether privacy-friendly sensors can deliver precise, real-time data on how traffic actually behaves at a complex urban junction. The aim was to gain better insight into interactions between cars, cyclists, pedestrians and public transport, in order to improve traffic safety and support smarter traffic management decisions.

The pilot in Mechelen was done to test how advanced lidar and AI technology can map and assess the condition of cycling infrastructure under real-world conditions. By scanning over 50 km of bike lanes and analysing surface quality, the city aimed to gain accurate data that helps identify maintenance needs, improve comfort and safety for cyclists, and support smarter investment decisions in its cycling network as part of its role in the Citcom.ai innovation programme.

The CitCom in Numbers article gives a snapshot of the scale and reach of CitCom.ai, highlighting the number of countries, partners, cities, testbeds and experiments involved. It shows how the initiative is building a strong European ecosystem to accelerate the testing and uptake of AI solutions for smart cities.