Epitel’s Pivot That Wasn’t: When Product-Market Fit Takes 15 Years to Prove

The startup playbook says if you haven’t found product-market fit in six months, pivot. Mark Lehmkuhle spent 15 years proving his founding insight was right. He never pivoted once.

In a recent episode of Category Visionaries, Mark Lehmkuhle, CEO and Founder of Epitel, a brain health technology platform that’s raised over $20 million, shared a journey that challenges every assumption about speed, iteration, and product-market fit. From 2008 to just four weeks before this conversation, Epitel built toward a single vision: create the wireless halter monitor for the brain. The insight never changed. The execution took longer than most startups exist.

The Insight That Started Everything

Mark’s founding observation emerged during grad school at the University of Utah in 2008. The comparison was stark and obvious: “Right now, you could walk into your neighborhood clinic and walk out with a wireless halter monitor for your heart. But your chances of getting a long term EEG anywhere, even if you go to your neighborhood hospital, is slim to none.”

This wasn’t a hypothesis requiring validation through customer interviews—it was an observable infrastructure gap. Cardiology had moved to wireless monitoring. Neurology was stuck with equipment that looked like “an old school recorder that looks like a vhs tape deck, and you got to wear that for three days. And you can’t shower or anything like that.”

The market size was massive: “One in ten people are going to have a seizure in their lifetime,” and epilepsy alone affects “3.4 million in the US. And to put that into perspective, the number of people with epilepsy is twice the number of people living with type one diabetes.”

The solution seemed straightforward: “We’re like, well, let’s just make the wireless halter monitor for the brain. And that’s kind of where we started.”

That vision never changed. What changed was Mark’s understanding of how long it would actually take to execute.

When Market Validation Takes Years

In software, you can build an MVP in weeks and test it with real users. In medical devices, you can’t beta test with patients. Mark describes the staged validation process: “We’ve got this dataset. We’ve trained our machine learning. We’ve gotten it through the FDA and as software, as a medical device, it’s good to go. But we’ve only ever recorded with these sensors in these very controlled environments in the hospital.”

Before commercialization, they had to prove the technology worked outside controlled settings: “What I’m telling you is that we want to get this outside the hospital for people so that they can live their lives and have this long term recording. So ultimately we had to run a number of pilots to prove to ourselves that, yeah, it’s good to go both in the hospital and outside the hospital as well.”

Each validation stage took years, not weeks. Hospital validation. Outpatient pilots. Regulatory submissions. Data collection. AI training. Each was necessary to prove the founding insight could actually be executed.

Traditional advice says if validation takes this long, you’re working on the wrong problem. But in regulated markets, slow validation is the only kind available. The question isn’t whether your insight is right—it’s whether you can sustain the organization long enough to prove it.

The Infrastructure That Couldn’t Be Rushed

One unexpected bottleneck reshaped Epitel’s timeline but validated their approach. When Mark needed training data for their AI, he discovered hospitals “just delete the data because we don’t have the storage for it.” The dataset he needed to purchase didn’t exist.

“So now we’re going to have to develop our own data set,” Mark realized. The company spent years collecting data where “we used the wired EEG as kind of the ground truth and then trained our machine learning on our sensor data.”

This delay would kill most startups. Investors would lose patience. The team would question the vision. But Mark understood something crucial: the infrastructure gap that forced them to build their own dataset was the same gap that proved their market thesis. If hospitals weren’t storing EEG data, it meant the current technology wasn’t enabling the long-term monitoring that patients needed.

The five years spent building a dataset wasn’t a detour—it was validation that the market lacked the basic infrastructure for long-term brain monitoring. A pivot away from this insight would have meant abandoning the problem at exactly the moment they’d confirmed how deep it ran.

The Artist Colony Test of Conviction

For years, Mark split time between the university and a company housed “literally in an artist colony because that’s the only thing that we could afford. So we’re building medical devices in an art studio in the heat of—the heat doesn’t work very well. The air conditioning didn’t work at all.”

He didn’t leave the university full-time until 2017, nine years after founding, “once we started demonstrating this traction.” The conventional wisdom says this proves the business wasn’t working. The reality: it proves Mark understood the difference between execution timeline and market validation.

The founding insight—that neurology needed the wireless monitoring cardiology already had—never required re-validation. What required time was building the technology, collecting the data, achieving regulatory clearance, and proving the product worked in real-world conditions. None of that questioned the core insight. All of it took longer than venture timelines allow.

Distinguishing Signal from Noise

How do you know when to pivot versus when to persist? Mark’s journey suggests a framework: separate market insight from execution challenges.

Market insight questions: Is there actually a problem? Do customers want it solved? Will they pay for a solution? For Epitel, these answers were clear from day one. The three-day wired EEG was terrible, seizures were common, and long-term monitoring would capture more events. No pivot required.

Execution questions: Can we build this technology? Can we collect the necessary data? Can we navigate FDA approval? Can we prove it works outside controlled environments? These questions took 15 years to answer, but answering them never required changing the core insight.

Most startup advice conflates these categories. If you can’t execute in six months, the advice is to pivot. But in regulated markets with long development cycles, execution timelines have nothing to do with market validation. The insight can be completely correct even if execution takes a decade.

The Funding Strategy That Matched the Timeline

Mark’s persistence was enabled by funding that matched his timeline. “We successfully did it on ninds grants and a few grants from the epilepsy foundation that allowed us to develop this technology and take it through the FDA. And it was all non dilutive,” he explains.

This funding strategy prevented the forced pivots that venture timelines create. “Any seed stage investor is just not going to see the return on that investment for a long period of time,” Mark notes. Venture economics would have created pressure to pivot toward faster revenue, even if it meant abandoning the core insight.

Grants enabled patience. Patience enabled validation. Validation took 15 years, but the insight was correct from day one.

When to Stick With It

When asked for advice on pursuing grants, Mark’s answer applies equally to the question of pivoting versus persistence: “To stick with it. If you truly think you have something innovative, all it takes is time. If you’re willing to put in the time, stick with it, you’ll get there.”

This isn’t blind optimism—it’s a framework for distinguishing between insights that need time to execute and ideas that are fundamentally wrong. Mark’s founding observation about the gap between cardiology and neurology monitoring was objectively true in 2008. It’s still true today. Fifteen years later, he’s finally bringing the product to market.

The question for founders isn’t whether to pivot after six months without traction. It’s whether your insight is about the market or about execution. Market insights that are wrong should lead to pivots immediately. Execution challenges that take years should lead to persistence, not pivots.

The Four Weeks That Validated 15 Years

Just four weeks before this conversation, Epitel launched commercially. After 15 years of building, the real test began: “We need to demonstrate that doctors want it, they’re buying it, they’re getting reimbursed for it through traditional channels, and they’re rebuying it,” Mark explains.

For Mark, who “never done before is sell anything,” this represents an entirely new challenge. “It’s super exciting and also really scary because I’ve never commercialized anything before.”

But the founding insight—that neurology needed what cardiology already had—isn’t being tested anymore. That was validated years ago through customer conversations, market research, and the simple observation that the three-day wired EEG remained the standard. What’s being tested now is whether Epitel’s specific execution of that insight can capture the market they always knew existed.

The Takeaway

Epitel’s story reveals when to pivot and when to persist. If your market insight is wrong—customers don’t actually have the problem you think they do, or they won’t pay for a solution—pivot immediately. But if your market insight is correct and only your execution timeline is long, persistence beats pivoting.

The challenge is matching your funding strategy to your timeline. Venture capital optimized for 6-12 month validation cycles will force pivots that abandon correct insights simply because execution is slow. Patient capital—whether grants, revenue, or strategic partnerships—enables you to validate insights on their actual timeline, not venture’s artificial one.

Mark spent 15 years proving one insight. He never pivoted. And now, finally, he’s bringing it to market.