Savana’s $44M Lesson: When Early Revenue Masks Missing Product-Market Fit

Savana’s $44M Lesson: When Early Revenue Masks Missing Product-Market Fit

By startup metrics, Savana was crushing it. Revenue in under twelve months. Working technology. Enthusiastic early adopters. Every signal said they’d found product-market fit.

They were actually weeks away from running out of money.

In a recent episode of Category Visionaries, Ignacio Medrano, Founder and Chief Medical Officer of Savana, revealed why early revenue became the metric that almost killed his company. For founders building in emerging categories, his story exposes a dangerous truth: revenue is a lagging indicator that can mask fundamental problems until it’s too late.

The Deceptive Win: Revenue Without Repeatability

Savana built breakthrough technology—natural language processing that could extract structured data from medical records and transform it into predictive insights. The value proposition was clear. Hospitals could finally use the information buried in their records to predict patient outcomes, identify treatment patterns, and make data-driven decisions.

Early traction came fast. “For us it wasn’t that long to generate revenue. Maybe I would say, less than one year,” Ignacio recalls. “So not bad to be healthcare.”

That first year of revenue felt like validation. In an industry notorious for long sales cycles and resistance to innovation, Savana had found buyers quickly. They had “early adopters and innovators that we found in a sector that is known for being very conservative.”

The checks cleared. Customers were using the product. By conventional startup metrics, they’d achieved the holy grail: revenue within the first year. VCs love that story. Founders build pitch decks around it.

But something was wrong. The second deal wasn’t coming. Neither was the third. The pipeline stayed empty while the bank account drained.

The Hidden Problem: Nobody’s Job

The breakthrough came not from analyzing what was working, but from confronting what wasn’t. Savana had paying customers, but they couldn’t find more of them. The technology delivered value, but there was no repeatable path to signing the next customer.

“When we launched this tool that is able to go to medical records, apply a lot of validated and scientific natural language processing,” Ignacio explains, “the idea was great, but then who would use it? And we found that it was no one’s job to use this kind of tool.”

This is the insight that changes everything about how to evaluate early revenue: Savana had built something valuable that didn’t map to any existing organizational role or responsibility.

In hospitals, there was no Chief AI Officer. No VP of Predictive Analytics. No budget line for medical record intelligence platforms. “And of course the budget were not big, especially in Europe where we started, so we had to pivot very quickly.”

Their early customers were anomalies—forward-thinking individuals who saw the potential and fought internal battles to allocate budget that wasn’t supposed to exist. But that doesn’t scale. You can’t build a $44 million company selling to organizational anomalies.

The revenue that felt like validation was actually a mirage. They’d found the 2% of the market willing to create new budget categories and organizational structures. The other 98% would never buy, no matter how good the product was, because adopting it required restructuring their entire organization.

Why Revenue Lies in Category Creation

Traditional product-market fit frameworks assume you’re entering an existing market. Customers have budget allocated for your category. There are decision-makers whose job includes evaluating solutions like yours. Competitive alternatives exist, which means the organizational infrastructure to buy is already in place.

Category creation breaks all those assumptions. You’re not just selling software—you’re asking customers to create new roles, new budget lines, new decision-making processes, and new organizational workflows. Early revenue can come from the tiny fraction of the market willing to do that work. But that fraction is never representative of the broader market.

“Different story is to get on the exponential curve, which you get in other businesses, but in healthcare it’s so much more difficult,” Ignacio notes. “But yeah, we cannot complain about the amount of early adopters and innovators that we found.”

The problem isn’t finding innovators. It’s mistaking their willingness to buy as proof that the broader market is ready. Early revenue from innovators doesn’t mean you have product-market fit—it means you’ve found the 2% who will buy before the infrastructure exists. The remaining 98% won’t follow until that infrastructure is built, which can take years or even a decade.

The Real Signal: Organizational Readiness

Looking back, Savana’s missing product-market fit signal wasn’t in revenue metrics. It was in organizational readiness. The right question wasn’t “Will customers pay?” It was “Does the organizational infrastructure exist to support buying decisions at scale?”

For Savana, the answer was clearly no. Hospitals didn’t have the roles, budgets, or processes to evaluate and adopt AI-powered medical record analysis. That infrastructure wouldn’t exist for another five years, not until COVID forced healthcare to accelerate digital transformation.

“And then only when the technology evolved, the mindset evolved, the culture evolved around the idea of data, healthcare data, intelligence, especially, sadly, thanks to the COVID situation. Only at that moment, the hospitals were ready to catch up with budgets and with people waiting to use our tools.”

What changed wasn’t the technology or the value proposition. What changed was that “it was no one’s job” became someone’s job. New roles were created. Budget priorities shifted. The organizational infrastructure to support Savana’s category finally existed.

The Framework: Three Tests Beyond Revenue

For founders building in emerging categories, revenue alone can’t validate product-market fit. You need three additional tests:

The Organizational Role Test: Is there a specific person in your target customer’s organization whose job responsibilities include evaluating solutions like yours? If you’re creating a new category, the answer is probably no. That’s not necessarily fatal—but it means your sales cycle will require organizational restructuring, not just product evaluation.

The Budget Line Test: Do customers have existing budget allocated for your category, or are they reallocating budget from somewhere else? If every deal requires creating new budget categories, you’re selling to the organizational risk-takers, not the mainstream market.

The Repeatability Test: Can you articulate a systematic process for finding and closing customers 2-50, or did customers 1-5 require heroic, non-repeatable efforts? Early revenue from champions who fight internal battles doesn’t prove you can scale.

Savana failed all three tests, despite generating revenue quickly. They had paying customers but not product-market fit. The difference between those two things is everything.

The Decision: Pivot or Wait

Once you recognize that early revenue masks missing organizational readiness, you face a brutal choice: pivot to a customer where the infrastructure exists, or wait for your target market to mature.

Savana chose to pivot. “What we did was we started selling this to pharmaceutical companies because they really have this interest of knowing what is happening to patients by certain disease.” Pharma companies already had roles, budgets, and processes for buying real-world evidence insights. The organizational infrastructure existed.

For five years, Savana sold to pharma while waiting for hospitals to develop the organizational readiness they needed. “So we stayed there as a company for five years. We survived. We’re incredibly close to die, as probably every entrepreneur would tell you.”

That five-year detour kept them alive. But it required accepting that their initial revenue—that exciting twelve-month win—had been misleading. They didn’t have product-market fit with hospitals. They had early revenue from organizational outliers.

The Principle: Infrastructure Before Scale

The lesson isn’t that early revenue is meaningless. It’s that in category creation, revenue is a lagging indicator that can mask fundamental problems. Before revenue can scale, organizational infrastructure must exist: roles, budgets, processes, and cultural readiness.

You can generate early revenue by finding the 2% willing to build that infrastructure themselves. But scaling requires the other 98% to have it already in place. The gap between those two states can be years or even a decade.

“For us it was like a journey where went somewhere, then we had to go somewhere else. And then we came back,” Ignacio reflects.

For founders in emerging categories, that journey is the reality of category creation. Early revenue feels like validation. But the real validation comes when you can answer yes to a harder question: Is the organizational infrastructure in place for customers to buy at scale?

Savana’s answer was no for five years. Recognizing that reality—despite having revenue—is what saved the company. Sometimes the most important metric isn’t whether you have customers. It’s whether you have the right kind of customers, buying for the right reasons, in a way that can actually scale.