Authors: Bojan Stojkovski and Bogdan Iordache
As Maximilian Fischer‘s journey shows, innovation often arises from questioning the status quo. Trained as a mechanical engineer at ETH Zurich, he initially specialized in quantum materials and physical chemistry for photonic computers and later pursued a PhD in the same field.
During his studies, Max co-founded HackZürich, Switzerland’s largest hackathon, where the world of software development contrasted sharply with the slower pace of academic research. This was also one of the experiences that sparked his shift from academia to entrepreneurship.
In 2016 Max co-founded Actyx with a colleague from the Industry 4.0 sector. The company started by creating custom software for factories and grew into a developer platform that digitized processes at over 40 manufacturing sites.
Today, as co-founder and CEO of Deltia, Max focuses on using predictive analytics and data visualization to improve the efficiency of manual assembly lines. In this conversation, he reflects on the key moments that shaped his path and the way forward for European manufacturing in the Industry 4.0 era.
UV: How does a researcher become a founder? How did it happen to you?
Max Fischer: During my studies, I met a few guys from the University of Zurich and ETH, and we started HackZurich together. It was incredible to see about 700 people coming together over one weekend to build software prototypes. I found it fascinating how quickly you can create things with software, especially compared to spending 12 hours in a lab working on quantum materials, which may not have any real-world application for 10, 15, or even 20 years.
This experience made me reconsider whether academia was the right path for me. I had a friend from university who came from an entrepreneurial background, always driven to build something of his own. It was then that I realized how much more exciting software development felt to me, and I decided to put my PhD inside a company.
UV: You’ve had experience digitizing over 40 factories. How did these early experiences shape the vision for Deltia?
MF: We started the company in 2016 when everyone talked about digital manufacturing and industry digitization, but no one knew what it meant. Coming from university, we didn’t have much experience with how factories operated, so we began by building custom software solutions. Over time, this evolved into what I would call the first generation of digital tools. Many companies, including us, started creating basic applications, like tablet solutions for workers, integrating software into machines, or adding sensors to provide visibility and transparency into operations.
On one hand, these tools proved useful once implemented, offering insights such as line productivity and output. However, I also realized that even seemingly simple systems—like a tablet app with just four buttons for start, stop, pause, and interruption—could take up to six months to fully roll out because of the complexity of training workers and changing behavior on the shop floor.
This realization pushed me to think about a completely new type of technology. It was clear that the potential value was enormous—if you could solve these challenges, the impact would be tremendous. That insight led me to computer vision, which turned out to be an almost magical solution for this kind of problem.
UV: You’ve emphasized the importance of technology working alongside workers, not replacing them. How has this philosophy shaped Deltia’s solutions?
MF: That’s definitely a core belief of ours: while factories are becoming increasingly automated—and rightly so, given the growing difficulty in finding skilled workers—humans will always play a crucial role in manufacturing. That’s why we focused on digitizing human work to make manual labor more efficient and to help people learn complex tasks faster and more effectively. We strongly believe that the human process will never fully disappear, and our goal is to enhance it.
Workers, especially those with 20 or more years of experience on the shop floor, hold an incredible amount of know-how—often innovating on their own to improve workflows.
Unfortunately, this knowledge is rarely formalized and can only be passed down through one-on-one training. When these experts retire, they often return as advisors or consultants because their expertise is irreplaceable. Therefore, we aim to digitize this know-how, capturing and systematizing it so it becomes accessible to more workers and shop floor teams.
UV: In the early days of Deltia, how were you figuring out the product, addressing challenges, and getting familiar with factories and your potential customers?
MF: We had this idea of using cameras and computer vision to digitize factory processes, so the first thing we did was validate it. Instead of diving into the technical details, we created PowerPoint presentations showing the results—what kind of visibility and insights these cameras could provide to customers.
We then spoke with a few dozen manufacturing companies to gauge their reactions, assess the value, and understand which use cases were the most promising. While there are many processes you could digitize, like assembly, setup, or machine-focused tasks, we quickly learned that assembly stood out as a particularly interesting and valuable use case.
UV: How do you convince traditional companies to adopt modern Industry 4.0 solutions like Deltia’s video analytics platform?
MF: I mean, you always have to convince them, right? There are companies and people in manufacturing who are very open and eager to explore innovation. But when you introduce something new to the shop floor, it often requires gaining the support of many people. The shop floor is at the heart of manufacturing companies. While it’s usually said that these companies are conservative, there’s a good reason for it—because introducing new elements to the shop floor can interfere with operations and potentially reduce profits.
I think the most effective way to convince manufacturers is by demonstrating a solid return on investment (ROI). Showing the potential for ROI through improved KPIs, particularly cost savings, is the simplest way to get buy-in. It’s not enough to just talk about how AI works; you need to focus on the value you’re providing and the benefits you’re creating for the customer—the added value that Deltia represents. However, even if you provide value, there can still be pushback for other reasons.
UV: What kind of pushback do you usually get when trying to sell into a factory, and what worries or blockers do people typically have?
MF: For our specific solution, we use cameras as sensors to collect data, which is a novel concept since cameras are usually associated with surveillance. This brings up concerns about data privacy, especially among managers and work councils in Germany. They often question, if not worry, about this camera approach. It requires a lot of explanation to show how we’re using AI in a privacy-preserving way.
Additionally, there are discussions around data generation and bots in simple processes, which are usually manageable but can be affected by timing—what the current priority is for the company. Are they focusing on new products or areas of high market demand? If so, there’s usually a good opportunity for us to show how our technology can help improve efficiency.
However, if a company is struggling with low demand or low capacity, convincing them to invest in technology can be challenging because they’re more focused on survival than optimization.
UV: In this sense, what specific technologies and processes should industrial companies integrate to stay ahead in Industry 4.0?
MF: Computer vision is crucial, but I think the challenge for many companies is managing their data effectively. Often, there are silos of data, and they may not even realize how much data they have. Centralizing this data and providing end-to-end visibility and transparency is important, even though it’s a significant initial investment. For many companies, it’s becoming increasingly clear that this is necessary.
Ultimately, the technology itself isn’t as critical as understanding the problem or use case at hand. It’s about finding the right solution for that specific problem. Computer vision can be useful for digitizing processes, but it’s not a one-size-fits-all solution. Manufacturing companies should focus on identifying the KPIs they want to improve and the specific problems they need to solve—technology always comes second.
UV: What key KPIs do you believe manufacturers should focus on when adopting new technologies?
MF: It really depends on the company. Cost is a crucial factor for many, especially in highly competitive manufacturing environments. The differentiating factor can vary—if a company’s competitive advantage is quality, then focusing on quality KPIs makes sense. Alternatively, if it’s speed, then lead time might be more critical. Identifying specific KPIs that allow a company to stay ahead of the competition is essential.
Additionally, beyond achieving specific business outcomes with new technologies, organizations need to learn and gain experience with them. Even if a new technology isn’t successful initially, it’s a learning opportunity for the company. Again, there’s no one-size-fits-all KPI, so companies need to find what works best for them.
UV: Given the skilled labor shortage that’s developing, what are your thoughts on the issue, and how can Deltia step in to help address it?
MF: I think it’s a big problem that’s only going to get worse over the next three to five years. While manufacturing companies are feeling the impact to some extent now, the retirement of experienced workers will hit hard. To address this, Deltia is helping in two ways—by improving efficiency so fewer people are needed to produce the same output, and by digitizing knowledge.
This makes it possible for less experienced workers to take on more complicated tasks and reduces reliance on the human workforce. Ultimately, our goal is to automate certain tasks, further increasing productivity and flexibility in the face of a shrinking workforce.
UV: Looking ahead to five to ten years from now, how do you envision the future of manufacturing, particularly in Europe?
MF: Manufacturing will still be a significant industry in Europe; I don’t believe it will move entirely away. Looking at Central Europe and Germany specifically, the last decade has been too good in many ways—there hasn’t been enough pressure to innovate and improve efficiency. But now, there’s a growing demand for software and digital solutions as the need to automate and become more efficient becomes more pressing. In my opinion, this will make German and European manufacturing companies more competitive again.
I think we’ll see a lot of innovation on the product side within Europe, as there’s more pressure to develop new, innovative products and automated processes. This will likely lead to more decentralized, smaller factories around the world instead of everything being concentrated in China. Europe has excellent engineers and a strong manufacturing base, particularly in Central Europe, which gives us a good position to remain competitive.