DEEPEYES COO Jan Wansink discusses how computer vision reshapes process monitoring, regulatory compliance, and efficiency—from sterile pharma environments to high-tech production lines.
It’s a crisp autumn morning in Munich, and the chill in the air leaves no doubt that winter is coming. Inside the DEEPEYES offices, the atmosphere is focused yet inviting. Chris Nicolaes, a seasoned expert in the manufacturing industry, arrives punctually for his conversation with Jan Wansink, COO of DEEPEYES. The two meet in the company’s cozy kitchen, unusually quiet at this hour. With fresh coffee in hand, they exchange a few friendly words before settling into an open conversation about the challenges and opportunities shaping the future of manufacturing.
Chris: Welcome to today´s conversation Jan. You are the Managing Director of DEEPEYES, an AI company specializing in computer vision for error recognition and process optimization. Jan, good to speak with you.
Jan: Thanks for coming, Chris. I’m excited to share how our technology is changing the way manufacturers monitor and improve their operations.
Jan: You’re absolutely right—regardless of the sector, the stakes are high.
In sterile manufacturing, for example, even the tiniest contamination can lead to a complete batch being scrapped. In other industries, the challenge might be defective products, safety hazards, or wasted resources.
Machines already produce plenty of data, but human activities on the shop floor have always been harder to monitor. Traditional methods rely heavily on manual checks, which are not only time-consuming but also prone to error. And even when problems are detected, it’s often too late to prevent losses.
Chris: That sounds like a big gap. So how does computer vision help close it?
A Second Set Of Eyes That Never Blink
Jan: Computer vision AI offers continuous, non-intrusive monitoring. Think of it as having a second set of eyes that never blinks.
It captures video data, analyzes it in real time, and instantly flags anything unusual—whether that’s a process step being skipped, a piece of equipment malfunctioning, or a safety protocol not being followed.This turns what used to be invisible into valuable data. And when you have that data, you can improve quality, reduce errors, and optimize your processes.
Chris: I like that image—”a second set of eyes.” So this technology doesn’t just watch, it also warns, right?
Jan: Exactly. Instant warnings are one of the most powerful features.
If, say, an operator is wearing the wrong protective gear, or a product is placed incorrectly, the system can alert the team right away.
That means issues are resolved before they escalate. It’s a big shift from reacting after something goes wrong to preventing it in the first place.
Higher Efficiency – Lower Cost
Chris: Prevention must also have a big impact on costs.
Chris: I like that image—”a second set of eyes.” So this technology doesn’t just watch, it also warns, right?
Jan: Absolutely. When you prevent errors, you prevent waste, recalls, and downtime.
And because the system generates continuous data, it can also enable predictive maintenance. Instead of machines breaking down unexpectedly, you can anticipate problems and fix them proactively.
For example, in one case, our system detected tiny leaks in a bioreactor. By catching them early, the manufacturer avoided losing an entire batch and saved valuable production time. That’s a direct financial win.
Chris: That’s a powerful example. Speaking of data, regulatory compliance is a major concern, especially in industries like pharma and food. How does this technology help there?
Jan: Video AI takes compliance to the next level. It automatically creates a privacy-compliant, detailed record of everything that happens on the production floor.
This makes audits far smoother and ensures traceability.
Instead of scrambling to piece together what happened after an incident, you have a clear, objective history. That builds confidence—not only with regulators but also with customers.
Data for Continuous Improvement
Chris: That kind of transparency must also help with training or – how we call it today – continuous improvement.
Jan: Exactly. Where there’s data, there’s insight.
Every module we deploy generates information that can be used to optimize processes. It’s like having a dashboard for your entire operation.
Instead of hoping that things are running smoothly, you know—and you can take immediate action if needed.
Chris: Risk mitigation seems to be a recurring theme here.
Jan: Definitely. Manufacturing comes with a lot of risks—financial, safety, and reputational.
By catching errors instantly, you dramatically reduce the chances of batch failures, product defects, or safety incidents.
It’s about being proactive instead of reactive, which is especially important in highly regulated or high-precision industries.
Chris: Many manufacturers worry about scaling up without losing quality. How does computer vision support that growth?
Jan: Scaling is always tricky, but our technology makes it easier.
Because the monitoring is automated and data-driven, you can ramp up production while maintaining the same level of quality and consistency.
Plus, the system is flexible. If regulations change or new processes are introduced, we can adapt quickly—no need to rebuild everything from scratch.
Chris: So to sum it up, this isn’t just about automation. It’s about giving manufacturers the tools to see, understand, and improve their processes in real time.
Simpler Monitoring and Control
Jan: Exactly. AI is setting new standards across industries.
With DEEPEYES, we’re not adding complexity; we’re simplifying monitoring and control. More relevant data leads to smarter decisions, better quality, and ultimately, stronger customer trust.Our goal is to give manufacturers—whether in pharma, food, automotive, or electronics—the confidence that their processes are running at peak performance, every minute of every day.
Chris: That’s an exciting vision, Jan. Thanks so much for sharing how DEEPEYES is shaping the future of manufacturing.
Jan: Thank you, Chris. It’s been a pleasure.
The Interviewer: Chris Nicolaes is a highly experienced leader in the startup and technology sector. He has founded and successfully exited two companies and has served as CEO with two innovative B2B tech startups.
Jan Wansink: Jan, COO of DEEPEYES GmbH, has introduced numerous leading-edge technologies into worldwide markets with two successful exits. He holds a master´s degree in computer science from Leiden University (Netherlands).
What kind of challenges would you love to solve with computer vision? Where do you think smarter/automated visual insights could make your daily processes easier or more efficient?
