Interview With Thomas Knox, Co-Founder and CEO of Vitvio

In this edition of Founder Spotlight we’re featuring Thomas Knox, the Co-Founder and CEO of VitVio, a company pioneering the use of artificial intelligence and computer vision to transform surgical procedures and hospital operations. Channeling his expertise in AI and computer vision, Thomas set out to transform one of healthcare’s most critical—and inefficient—arenas: the operating room. Under his leadership, VitVio is deploying cutting-edge AI systems that automate administrative burdens, orchestrate surgical teams, and create digital twins of operating theaters, all with the goal of making surgeries safer, faster, and more efficient.

Driven by both personal conviction and technical mastery, Thomas Knox is not just building technology—he’s crafting a new vision for healthcare, where innovation and compassion work hand in hand to save lives and elevate patient care.

Thank you for joining us! You’ve transitioned from helping hyper-growth startups soar in value to enhancing life-saving efficiencies in surgery rooms. What have been the major shifts in your mindset and approach?

Moving from retail tech to healthcare has been an incredible shift, both in mindset and responsibility. In retail, the focus was all about convenience and cost—how quickly can we get a customer in and out, how seamless can we make their experience? But in surgery, it’s not about speed for speed’s sake; it’s about precision, efficiency, reliability, and ultimately, patient safety.

The biggest change for me has been learning to work within a system where lives are on the line. There’s no room for “move fast and break things” in an operating room. Every piece of technology we develop needs to be rigorously validated, seamlessly integrated, and, most importantly, fully trusted by the people using it. That has shaped the way we build our AI—working hand-in-hand with surgeons, making sure our solutions are actually useful, and ensuring that the tech disappears into the background, supporting their work rather than interfering with it.

Computer vision in surgical settings requires extremely high accuracy and reliability. What steps do you take to ensure the AI algorithms perform consistently and safely under various conditions?

It starts with the data. We make sure our AI is trained on real-world scenarios, accounting for different hospitals, different lighting conditions, and different ways surgical teams operate. But beyond training, it’s about real-time adaptability—our system doesn’t just make a prediction and stop learning. It continuously refines its insights based on what’s happening in the OR.

We also build in multiple layers of validation. Every insight our AI provides comes with a level of confidence, and we always ensure that human oversight is central. AI should never be making decisions on behalf of surgical staff entirely—it should be assisting them, providing clarity when things get complex. We build systems that allow the staff to always have complete transparency and control in case they disagree with our predictions.

And of course, there’s the regulatory side. We work closely with hospitals, research institutions, and regulatory bodies to ensure our tech meets the highest standards. In healthcare, trust is everything, and that trust comes from knowing a system is not just smart, but also safe and reliable.

With the increasing focus on AI in healthcare, what are the key differentiators that set VitVio apart from competitors in the market?

Most AI in healthcare focuses on post-operative analysis—looking at data after the fact and identifying areas for improvement. While that has its value, it doesn’t help when a problem is unfolding in real-time. What sets VitVio apart is that we bring AI directly into the operating room, enabling teams to act in the moment, not just analyze afterward.

We start by digitalizing the operating room in 3D, mapping out everything that’s happening—who is doing what, when, where, and why. This real-time understanding allows us to deploy AI Agents on top of that data, automating the administrative tasks that often slow down surgical teams. Instead of staff being bogged down by logistics, scheduling conflicts, or documentation, our system handles those burdens, ensuring the entire team stays focused on what truly matters—the patient.

What makes this truly impactful is the way we integrate. We don’t introduce extra complexity or demand that hospitals overhaul their workflows. Our technology works within existing systems, fitting naturally into how teams already operate. AI in surgery isn’t just about automation; it’s about trust, efficiency, and ensuring that technology amplifies human expertise rather than replacing it.

What are the key performance indicators (KPIs) you use to measure the success and impact of VitVio’s platform in hospital operating rooms?

It all comes down to making surgeries run more smoothly. We look at how much of an operating room’s available time is actually being used for procedures, how quickly teams can turn over between surgeries, and how well hospitals are able to stay on schedule.

We also pay close attention to delays—whether that’s missing instruments, scheduling conflicts, or unexpected complications. If we can reduce those bottlenecks, it means more patients get treated and hospitals run more efficiently at higher margins.

Beyond the operational side, we also track the impact on patient outcomes. While this aspect is still very early on within our solution, we have our eyes set on looking at if we are helping to reduce avoidable complications. Are fewer patients needing to be readmitted? Those are the kinds of real-world impacts that matter most. What’s most interesting to me here is that we can have a substantial impact even just by alleviating the staff’s administrative burden. It should not come as a shock to any of us that having staff focus purely on the patient, can lead to better outcomes.

Integrating AI into clinical practice presents challenges. What are the most significant ethical considerations you’ve encountered at VitVio, and how have you addressed them?

The biggest challenge is trust. In an industry like healthcare, AI can’t be a black box—it has to be fully transparent. Surgical teams need to understand how the system reaches its conclusions, and they need to be able to override it whenever necessary.

Another major consideration is privacy. Hospitals are rightly cautious about how data is handled, so we’ve built our system to anonymize information and, whenever possible, keep processing on-site. That means hospitals stay in full control of their own data, without it being sent off to external servers.

Bias is another concern. AI is only as good as the data it’s trained on, so we work to ensure that our models reflect a diverse range of surgical settings and demographics. The last thing we want is a system that works well in one hospital but fails in another because it wasn’t trained on enough variety.

At the end of the day, AI in healthcare has to be designed around people—ensuring that the technology is working for them, not the other way around.

How do you see VitVio evolving beyond surgical procedures? Are there other areas in healthcare where you believe your AI-driven computer vision platform could be applied?

Surgery is just the starting point. The technology we’ve built—tracking processes in real-time, providing intelligent insights, and helping teams coordinate more effectively—has applications across the entire hospital.

There’s potential in emergency rooms, where quick decision-making is critical. There’s also an opportunity to help with post-surgical recovery, ensuring patients get the right care at the right time. Even areas like medical training could benefit, using AI to provide real-time feedback to surgeons in training.

Our goal is to help hospitals run more efficiently, wherever that’s needed. If we can improve how medical teams work together, we can ultimately improve outcomes for patients.

What strategies do you use to build trust and encourage adoption of VitVio’s platform among surgeons and other medical staff who may be hesitant to embrace AI in their work?

It starts with collaboration. We don’t build in isolation—we work directly with surgeons, nurses, and hospital administrators to ensure what we’re developing actually fits their needs. If AI is going to be used in an operating room, it has to be something the medical team believes in and feels comfortable using.

We also focus on transparency. We make sure staff can see exactly why the AI is suggesting something, so they remain in control.

And of course, training is key. We don’t just drop new technology into a hospital and expect people to figure it out. We run hands-on sessions, provide real-time support, and ensure that teams feel fully confident before they start using our system in live procedures.

Congrats for $2 million in pre-seed funding! How do you plan to allocate resources to expand the platform’s capabilities?

This funding is a crucial step in expanding what we’ve built and making sure it delivers real impact in hospitals. The priority is on refining our core technology—ensuring that our AI is as accurate, reliable, and adaptable as possible across different surgical settings. That means investing in further development, particularly in areas like real-time tracking and predictive analytics, so hospitals can not only react to issues faster but anticipate them before they become problems.

Another key focus is clinical validation. In healthcare, proving effectiveness isn’t just about technical performance—it’s about demonstrating measurable improvements in surgical efficiency and patient outcomes. We’re working closely with hospitals to run real-world pilots, collect data, and ensure that our platform is meeting the highest standards.

Beyond that, we’re scaling our operations to support wider adoption. That includes strengthening our integrations with hospital IT systems, expanding our deployment capabilities, and making sure that when hospitals bring VitVio on board, the transition is seamless. Ultimately, this funding is about taking what we’ve proven works and making it accessible at scale.

Given VitVio’s innovative technology, what valuation methodologies and metrics do you employ during fundraising, and how do you address the unique challenges of valuing a healthtech startup?

Valuing a healthtech startup is different from other industries because the path to adoption isn’t just about market demand—it’s about clinical validation, regulatory approvals, and integration into complex healthcare systems. The approach we take is a mix of understanding the scale of the problem we’re solving, the efficiency gains we enable for hospitals, and how that translates into long-term growth.

Investors look at a few key factors. First, the market opportunity—surgical inefficiencies are a massive challenge globally, and AI-driven solutions that can improve workflow and reduce delays have significant potential. Then there’s the traction we’re building—our ability to secure partnerships with hospitals, run successful pilot programs, and demonstrate real-world impact.

Healthtech also requires a different kind of patience from investors. Unlike in pure tech, where you can move fast and iterate, healthcare requires rigorous validation and compliance with strict regulations. That’s why we focus not just on growth metrics, but on building a strong foundation for long-term adoption. The goal isn’t just to scale quickly, but to do so in a way that’s sustainable and trusted by the medical community.

What advice would you give to other entrepreneurs looking to apply AI and computer vision to solve pressing problems in healthcare?

Solve a real problem. AI is exciting, but technology for technology’s sake doesn’t work in healthcare. You need to understand the pain points—what’s actually slowing doctors down, what’s causing inefficiencies, where hospitals are struggling. Start there.

Before we ever wrote a line of code, we conducted hundreds of interviews with a wide range of people in healthcare. We always say that VitVio was not our idea, but was rather the idea born from the hospital directly via the insights we gathered.

Second, build with the people who will actually use your product. Too many AI startups assume they know what’s best for healthcare without talking to the people on the front lines. Work alongside them, get their input, and make sure what you’re building fits into their world rather than forcing them to change how they work.

Finally, be patient. Healthcare is a highly regulated industry, and adoption takes time. But if you build something that truly makes a difference, the impact is enormous.