I first met Franz Tschimben three years ago in Berlin, at one of those sparse, under-heated startup events where everyone looks slightly uncomfortable. He wasn't doing the typical founder pitch thing. No deck, no rehearsed narrative. Just questions. About what we were seeing in the market, what was actually dumb versus real, why everyone seemed to be talking past each other. That conversation stuck with me.

So I went back to Südtirol. To meet not just Franz, but Harald Oberrauch and Burkhard Güssefeld, the team that built what might be the most unglamorous, most necessary infrastructure company in AI right now. We sat in a room in Bolzano on a gray afternoon. Coffee. No PR.

The 3D Data Factory

Franz Tschimben (CEO) returned to South Tyrol after a decade in Silicon Valley including a checkout-tech startup in San Francisco he shut down after two and a half years when product-market fit didn't arrive; Burkhard Güssefeld (CTO) has followed a teenage obsession with graphics cards and light physics all the way into computer vision and 3D reconstruction; Harald Oberrauch (President) brings decades of industrial company-building from the region. ALLSIDES was founded out of Covision Lab, an AI research centre in Bolzano. Together they are building what they call the 3D Data Factory: fully automated, physically accurate capture of real-world objects at industrial scale. The timing couldn't be better. The market for AI training data is projected to reach nearly $10 billion by 2029, and physically correct 3D has become the critical bottleneck inside it.

The Wrong Market, Twice

Burkhard was convinced early on: by gaming. “In the late 90s I was obsessed with graphics cards, GPU technology, shaders. The gaming industry had massive demand for realistic 3D assets. I thought that's the market.” Except gaming doesn't work that way. They build most assets themselves. They weren't paying for photogrammetry services. The real urgency was e-commerce: Amazon rendering millions of products, Nike needing every shoe in every angle. But even that wasn't the full story.

Two years in, the labs started coming: Meta, OpenAI adjacents, robotics companies. Asking for data that can teach machines how the physical world actually works. “That's when we realized,” Harald says, “we weren't building a 3D content company. We were building infrastructure for the next generation of AI.” All three shake their heads when I ask if they saw it coming.

Nearly all classical computer vision algorithms rest on brightness constancy: the idea that an object looks the same from every angle. It is also physically wrong. Velour reflects light differently than polished metal. Pearlescent surfaces shift colour with viewing angle. The data is broken before it is ever used. ALLSIDES inverts the logic. Those variations are treated as signal, not noise. A single ALLSIDES scanner now produces more than 30,000 physically accurate 3D models per year.

“The algorithm is maybe 30% of the problem. The rest is: how do you actually capture reality in a way that's useful? That's hardware. That's calibration. That's the entire data pipeline.”
— Burkhard Güssefeld

The Failure That Changed Everything

Franz had failed before. AKER, which was basically Amazon Go for smaller supermarkets. He spent two and a half years in San Francisco. “We had Timing. We had Team fit. We didn't have real product-market fit. We had something customers found interesting, but not something they needed to pay for. And the founding team; we were good people, but we weren't right for each other. Those misalignments matter.”

“In that moment, it felt brutal. Like a personal failure.”
— Franz Tschimben

The consequence for ALLSIDES was one hardcoded constraint: objects only. No faces, no full environments, even though those categories attracted more attention and more funding. Franz and Burkhard ended those conversations early. Within six months they had designed, manufactured, and deployed their first scanners with Adidas, Zara, and Meta. Companies that expect 24/7 operation from day one. Early investors were sceptical: hardware is read as a liability in the current AI climate. What changed their minds was not the argument. It was what the hardware demonstrably produced. The perceived liability turned out to be the moat.

The first moment of real doubt came early. “We had a technology that worked in the lab. But 3D models already existed everywhere,” Franz says. “There were days where I thought: maybe we're solving a problem nobody actually has.” What changed it was Adidas. They looked at what ALLSIDES could do and said: ‘This is what we need.’ Not ‘this is interesting.’ Not ‘this is cool.’ “Once you have one customer at that level saying yes, actually saying yes with money and not just compliments, everything shifts,” Burkhard adds. “You know you're not crazy.”

Physical AI Needs a First Mile and It Has to Be Right

The shift in how ALLSIDES understood itself happened through Meta. Meta used ALLSIDES to build a digital twin catalogue and the data was immediately picked up as training material by robotics companies and physical AI labs. This is the real danger of the sim-to-real gap: a model trained on physically incorrect data fails the moment it meets an actual object. That gap cannot be patched downstream. The data has to be right before anything else happens.

The vision is to do for 3D data what NVIDIA did for compute, by becoming the underlying layer without which the next generation of AI systems cannot function. The market for AI in robotics alone is projected to exceed $180 billion by 2033. “How to be a platform, not just a tool,” Franz says when asked what they're still figuring out. “How to build something that other people can build on top of. That's the next phase.”

“The market tells you what you're building. If you listen.”
— Franz Tschimben

They're not claiming to have invented 3D. They're claiming to have solved the infrastructure problem that nobody else wanted to touch. That's the difference between a company and a footnote.

How a Place Changes What You're Building

We're in a small pizzeria in Bolzano's old town, the kind where they know the regulars by name. It's late, the tables around us half-empty. I bring it up casually while we're waiting for food.

“You could have built this anywhere,” I say. “Why stay?”

Franz smiles. Harald doesn't hesitate.

“I never left. But growing up here, watching companies stay relevant for decades instead of burning out. That teaches you something about patience. About building things that last, not just things that grow.”

He pauses. “That's not the Valley. The Valley optimizes for growth. Here, people optimize for durability. Relevance.”

Burkhard nods. “I moved here deliberately. With kids, a life outside work. That changes how you think about what you're actually building.”

Franz adds something quietly: “I left for ten years. Needed to see what ambition actually looks like at scale. But when you come back…” He trails off. “You don't unlearn things. You add to them.”

“So when we started ALLSIDES,” Burkhard continues, “people kept calling with bigger ideas. Faces, environments, generative 3D. We said no. Objects only. Perfect objects.”

I ask why.

“You're not building for a story,” he says simply. “You're building because something needs to exist.”

Harald picks this up: “Most tech companies can't think like that. The pressure is too intense. But there's something about this place that lets you stay focused. You're not competing on hype. You're competing on clarity.”

He grins slightly. “Even if you're opening an office in New York next month.”

The point lands: rooted doesn't mean limited. They're building a global company, but they're building it from a place that keeps them honest.

The wine arrives. We move on to other things: kids, the mountains, how the city has changed. But something stays with me: these three didn't come to Südtirol to be romantic founders. They came because the place forced them to ask better questions about what they were building.
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14 Months Later

As I'm writing this report, I think back to that Berlin conversation. Franz asking questions instead of pitching. Skeptical. Curious in a way that felt almost uncomfortable for a founder.

What strikes me now is that same quality hasn't changed. He's still asking the hard questions. Still skeptical about the narrative. Still uncomfortable with hype.

That matters more than it sounds.

There's a type of founder who becomes convinced of their own story. Starts believing the hype. Starts optimizing for the narrative instead of the problem. I've seen it happen a dozen times. Companies that had real technology, real customers, real traction, and then just… stopped learning and listening.

Franz, Burkhard, and Harald haven't done that. They still talk about what they got wrong. They still adjust when the market tells them something new. They still act like people who are solving a problem, not people who already have all the solutions.

Harald said something lately: “We're not done. We've just started.”

Most founders say that. With these three, I believed it.

Redstone invested in ALLSIDES because the company addresses the first-mile problem of 3D data capture, a structural bottleneck understood for decades, never systematically solved and arrives precisely as physical AI and generative 3D shift from experimental to critical infrastructure.