The Swiss Data Science Center (SDSC) supports SMEs in their digital transition through a range of assistance programs. Silvia Quarteroni, Head of Innovation, explains how the organization bridges the gap between academia and the business world, enabling research projects to find concrete applications within companies.
Established through a collaboration between EPFL and ETH Zurich, the Swiss Data Science Center (SDSC) has held the status of national research infrastructure since 2025. In this capacity, it contributes to the Confederation’s efforts to accelerate the use of data science and artificial intelligence within the ETH Domain, the broader Swiss academic community, and the industrial and public sectors. The SDSC, which today employs more than 120 staff and also includes the Paul Scherrer Institute (PSI), offers support programs for SMEs in collaboration with the cantons of Vaud and Zurich. Silvia Quarteroni, Head of Innovation at the SDSC, stresses the strategic relevance of these topics for the competitiveness of Swiss companies.
How does the SDSC support SMEs?
Silvia Quarteroni: Each year, we launch a call for projects for our support programs in areas such as public administration and digital transformation, as well as biomedicine, the environment, and energy. The first support program is funded by the canton of Vaud and enables us to provide SMEs with our technical expertise and financial support to carry out their projects. We also have a partnership with the canton of Zurich, which focuses more on organizing AI workshops and connecting SMEs to encourage collaboration. In the longer term, we hope to extend these programs to other cantons. Any company can also approach us at any time on a mandate basis to implement an AI project. We also support SMEs in applying for funding programs, such as those offered by Innosuisse.
What do your programs involve in practical terms?
Quarteroni: We do not provide turnkey solutions. Instead, we work alongside SMEs to address issues that have been identified in advance. In most cases, the projects we develop with SMEs build on products that already exist within the company. Each program begins with an introductory phase aimed at drawing up a roadmap. This makes it possible to define the project’s objectives, identify the data required, and lay the groundwork for seeing the project through to completion. We then support SMEs over a period of six or twelve months, depending on their needs. This phase is essential because artificial intelligence is often associated exclusively with LLMs (Large Language Models) such as ChatGPT, Claude, or Gemini. Yet the foundation of AI lies primarily in data management and data quality. It is therefore crucial for companies to clearly identify the relevant data at their disposal and define its practical applications.
Once the issue has been defined, we develop a tailored AI model, for example, to predict product quality or detect potential defects. In general, two SDSC engineers are assigned to each project, with regular follow-up through weekly or biweekly meetings, with the aim of ultimately bringing the product into operation. This final stage is usually carried out by the company’s own IT department or by external IT providers.
Are there particular areas where demand is especially strong?
Quarteroni: A recurring request concerns optimizing energy consumption. Many industrial SMEs face this type of challenge. The interest is twofold: reducing costs and meeting ESG sustainability objectives. For this type of project, different categories of data are required: the building’s structure, its maintenance history, current energy consumption standards, and heat distribution modelling. To address these issues effectively, collaboration with local partners is essential. That is why we often work closely with universities and cantonal universities of applied sciences, which possess these applied competencies.
Who is eligible to apply?
Quarteroni: Applicants must be established in the cantons of Vaud or Zurich. However, collaboration with a company or school located outside the canton is possible, provided that the main project partner is based in one of the partner cantons. Our support is most relevant for SMEs that demonstrate curiosity about artificial intelligence and data management, even if they do not yet have in-depth expertise in these areas. Applications are assessed by a jury external to the SDSC to avoid any conflicts of interest. The criteria include the degree of innovation, the project’s societal impact, and its feasibility.
What would you say to SMEs that remain hesitant about using AI?
Quarteroni: The biggest mistake is assuming your company has nothing to do with artificial intelligence. AI is a cross-cutting technology that can be relevant to virtually any SME. Rather than being forced to undergo this shift, companies can choose to view it as an opportunity. The objective is not to implement AI at any cost, but to understand how data can support better decision-making. Some projects fail because SMEs attempt to imitate the technology giants. It is often far more effective to start modestly, clearly identify your needs, and move forward step by step.
