7 Go-To-Market Lessons from 10 Years Building Healthcare AI

7 Go-To-Market Lessons from 10 Years Building Healthcare AI

Ignacio Medrano spent five years selling to the wrong customer. It nearly killed his company. But that detour taught him more about go-to-market strategy than any playbook could.

In a recent episode of Category Visionaries, Ignacio Medrano, Founder and Chief Medical Officer of Savana, shared the hard-won lessons from building a healthcare AI company that’s now raised $44 million. These aren’t the sanitized success stories you read in press releases. These are the mistakes, pivots, and counterintuitive insights that only come from surviving a decade in one of the most challenging markets in B2B tech.

Lesson 1: Revenue Doesn’t Mean You Have Product-Market Fit

Savana generated revenue in less than a year. By startup standards, that’s exceptional—especially in healthcare. But Ignacio learned that early revenue can mask a fundamental problem: you might be solving a problem that nobody’s job is to solve.

“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.”

The technology worked. The value proposition was clear. But hospitals didn’t have budget owners or decision-makers for this category. Savana had built something that fell between organizational cracks. Revenue from early adopters created the illusion of traction, but it wasn’t sustainable go-to-market motion.

The lesson? Validate not just that customers will pay, but that your solution maps to existing organizational structures, budgets, and job responsibilities. If you’re creating a new category, you’re also creating a new buying process—and that takes exponentially longer.

Lesson 2: Pivot to Where the Budget Lives (Even If It’s Not Your Vision)

Facing extinction, Savana made a pragmatic pivot that saved the company: they started selling to pharmaceutical companies instead of hospitals. Same core technology—natural language processing that extracted insights from medical records—but a completely different customer with actual budget allocated for this type of intelligence.

“We stayed there as a company for five years. We survived. We’re incredibly close to die, as probably every entrepreneur would tell you,” Ignacio admits.

This wasn’t the original vision. It didn’t have the same impact potential as transforming hospital operations. But it kept the lights on while the market matured. For five years, Savana sold de-identified patient data insights to pharma companies eager to understand real-world disease progression.

The lesson? Sometimes the right go-to-market strategy is staying alive long enough for your original market to be ready. That might mean serving an adjacent customer that has budget today, even if they’re not your dream customer. Strategic pivots buy you time.

Lesson 3: Kill Products That Users Reject, No Matter How Elegant the Logic

Savana Consulta was built on impeccable logic: doctors could see what their peers were doing in real clinical practice and make decisions based on collective wisdom. It was like digitizing clinical rounds where physicians discuss cases and learn from each other.

“We thought that was a good idea. We were thinking about the wisdom of the crowds, the idea that if many people are thinking about that, it means something,” Ignacio says.

The market rejected it brutally. “It was incredibly rejected by my colleagues. And the reason was very simple. The fact that the majority is doing something doesn’t mean it’s the right thing to do. And that’s quite opposite to what Evidence means.”

Savana had accidentally positioned itself against evidence-based medicine—the foundation of modern healthcare. They were suggesting doctors follow what most people do rather than what research proves works. “In a way, were trying to go against the status quo, which is using the right evidence instead of using the majority, the wisdom of the majority.”

They killed the product and rebuilt using the same technical capabilities for a fundamentally different purpose: creating evidence-based reports that supported, rather than replaced, clinical decision-making.

The lesson? Elegant logic and sound technology don’t matter if you’re fighting against your market’s core principles. When users tell you something doesn’t work, listen to why—not just what. The underlying principle they’re protecting might be more important than you realize.

Lesson 4: Market Timing Beats Perfect Execution

For five years, Savana’s original vision—selling directly to hospitals—wasn’t viable. The technology worked. The value was demonstrable. But the market wasn’t ready.

Then COVID hit. “Only at that moment, the hospitals were ready to catch up with budgets and with people waiting to use our tools,” Ignacio explains. “And that’s how we came back somehow to the original idea.”

The pandemic didn’t just create urgency around healthcare technology. It fundamentally shifted mindsets about data, digital tools, and AI in clinical settings. Budget priorities changed. New roles were created. What wasn’t anyone’s job in 2015 became essential infrastructure by 2021.

The lesson? You can’t force market timing, but you can position yourself to capitalize when the moment arrives. Savana stayed alive in pharma for five years, kept developing their core technology, and maintained relationships with hospitals. When the market shifted, they were ready to move immediately.

Lesson 5: Healthcare Buying Decisions Are Fundamentally Irrational

This is the insight that separates healthcare founders who succeed from those who flame out after a year. “What differentiates healthcare is that a bigger amount of decisions that your customers will make will not be based on the rational laws of the market,” Ignacio says.

He’s seen it repeatedly: software that clearly optimizes operations gets adopted, but the headcount reduction it enables never happens. “A typical case would be you optimize something with which you need, I don’t know, 10 nurses less. And it doesn’t really matter because politically it’s against everything not to count on 10 nurses.”

The result? “You come with an innovation that apparently is useful, but then at the end of the day, you have double expense. You now have the software and you have the people, and that keeps replicating and replicating in the sector.”

The lesson? Build your business model assuming customers will keep their existing costs even after adopting your solution. Your ROI story can’t depend on headcount reduction or cost elimination. Look for value creation, not cost replacement. Factor political and social dynamics into your sales cycle expectations.

Lesson 6: Match Your Capital Strategy to Your Market’s Timeline

Savana has raised $44 million, but Ignacio is frank about the tension between healthcare timelines and typical VC expectations. “The pace is lower so it’s very regulated. Cultural change needs time. And even if your tool is great, it’s going to need time.”

Traditional venture capitalists expect returns in three to four years. Healthcare often needs longer. “We have incredible new drugs that would save lives. And even when that’s the case and it’s lives of people, what is at stake, it takes 10 years to validate them through the proper workflow circuitry,” Ignacio points out.

“For us and for any company in healthcare, it’s very difficult to give returns. And in that amount of time you normally, you need longer. So that’s something that you may want to think about before fundraising.”

The lesson? Be strategic about which investors you bring on. Look for firms with healthcare experience who understand these timelines. Consider alternative funding structures. Set expectations explicitly about timeline to scale. The wrong investor isn’t just unhelpful—they can create pressure that forces premature decisions or unrealistic pivots.

Lesson 7: Wait for Scientific Validation Before Going Broad

Ten years ago, Ignacio explained machine learning to skeptical colleagues in his hospital cafeteria. “I remember telling this story and they were looking at me like, yeah, that’s cool stuff, but it’s never going to work. I mean, we’re in science, we’re in proper statistics, you need proper methods.”

Today, AI in healthcare is mainstream. But the lesson isn’t about being early. It’s about patience for validation. “The machine learning AI algorithms that we’ve been creating for five, 10 years, five years from now, will be finally validated with clinical trials and everything,” Ignacio predicts. “Something that we don’t have today, but we’ll have it in five years.”

Until you have that clinical validation, your go-to-market strategy needs to account for skepticism. You’re not just selling software—you’re selling a new epistemological approach to medicine. That requires proof at a different standard than other B2B markets.

The lesson? In regulated industries with high stakes, time your aggressive growth phase to coincide with definitive validation, not just promising results. Early adopters will take you on faith, but scaling requires evidence that meets your industry’s burden of proof.

The Through Line

What connects these seven lessons? They’re all about recognizing that healthcare operates on fundamentally different principles than other B2B markets. Financial logic doesn’t always apply. Decision cycles are longer. Scientific validation matters more than customer testimonials. Market timing can make or break you regardless of execution quality.

“Considering that not because something makes sense is going to be accepted by healthcare providers, I think is good advice,” Ignacio says.

For founders building in healthcare, that’s not pessimism—it’s realism. And realism, as Savana’s decade-long journey shows, is what keeps you alive long enough to win.