7 Go-to-Market Lessons from Selling AI to Pharma’s Most Conservative Buyers

Most B2B founders selling to conservative industries face a brutal paradox: You’ve built something that solves a massive problem, but when you pitch it to the people who need it most, they look at you like you’re speaking a foreign language.

In a recent episode of Category Visionaries, Dimitrios Skaltsas, CEO and Co-Founder of Intelligencia AI, shared how his team cracked this code in pharmaceutical drug development. Their journey from a “shoebox apartment in New York” to a cash flow positive AI platform that’s raised $15.5 million offers a masterclass in go-to-market strategy.

Here are seven lessons that apply to anyone selling complex technology to skeptical buyers.

Lesson 1: Build First, Sell Later—Even When You’re Burning Cash

Most founders hear “talk to customers early” and interpret it as “sell before you build.” Dimitrios took the opposite approach.

“We started product first, and for many years, actually, we have retained that money, but we built something,” he explains. They launched in fall 2017 and didn’t start reaching out to customers until they had real results in late spring 2018.

In pharma, where innovation propensity is “unfortunately a bit backwards” outside of core drug development, you need proof. Their first customer, a major pharmaceutical company, signed in early 2019 because the results were already there.

Lesson 2: Accept That Conservative Industries Speak a Different Language

Dimitrios describes those early sales conversations by referencing Moneyball: “You’re this, in many ways, you’re this toppy young guy who, you know, speaks a different language, and people are not sure they get it right.”

The pharmaceutical industry was making billion-dollar decisions using benchmarks and expert opinions—what Dimitrios calls “suboptimal” approaches. “You have this paradox where science is trade season making. Science is suboptimal, it’s not evolved enough.”

The insight: Don’t make customers feel stupid about their current process. Intelligencia AI positioned themselves as partners who could enhance what was already there, working within the culture while pushing boundaries incrementally.

Lesson 3: Your Best Early Customers Are Building New Things Within Old Structures

Intelligencia AI’s first customer wasn’t a scrappy biotech startup. It was a major pharmaceutical company—specifically, their external innovation function.

“They were building this external innovation function where it’s a function where they look for new drugs from smaller companies, from biotech, and by default, they were building something that was forward looking and they want to embed. Innovate elements were the perfect match,” Dimitrios explains.

Find the innovation pockets within conservative organizations. They have budget, problems worth solving, and political capital to try something new.

Lesson 4: “Listen to Your Customer” Isn’t Enough—You Must Embed in Their Workflow

When asked about his most important GTM lesson, Dimitrios says something that sounds simple but isn’t: “Listen to your customer again and again.”

But listening alone doesn’t cut it. The real breakthrough came when Intelligencia AI shifted from building what they thought was ideal to building what actually fit into how people work.

“A great solution is not enough. Ultimately, any company wants to have impact, right? You won’t have customers, you won’t have users,” Dimitrios explains. The key was learning “how to embed it in the workflow of users, how to build the right functionalities around this, how to, you know, move yourself a bit from being a purist, if you will, to what the users exactly need.”

This is the difference between impressive technology and technology that gets adopted. Build for the workflow, not for the demo.

Lesson 5: Navigate the Hype Cycle by Going Deeper Than the Noise

ChatGPT’s explosion in late 2022 created an unexpected challenge for Intelligencia AI. While most AI companies celebrated, Dimitrios saw the downside: “There are pharmaceutical companies actually are kind of shutting down or shutting out subject from their organizations because they’re like, okay, we cannot trust it yet, so don’t use it literally.”

The noise made everyone an AI company overnight. So how do you differentiate? Go deeper.

“People who use both or multiple solutions, you know, they turn, tell us, okay, you’re not real competitors, because you do. Actually, I go deep where some of the cases, it’s a touch AI,” Dimitrios says. The market is getting smarter about distinguishing real AI from marketing AI.

The second differentiator: explainability. “These are highly sophisticated users who want to understand and actually embed AI into their own pattern recognition, into their own decision making,” he notes. Black boxes don’t work with sophisticated buyers. Transparency builds trust.

Lesson 6: Treat Fundraising Like a Drug—Powerful But Potentially Addictive

Dimitrios has a nuanced take on venture funding: “Sometimes I joke funds is our track in a good way. It’s something you need survive, especially in the early days, especially if you build technology as we did… At the same time, I call it a drug because you can also become dependent on this.”

Intelligencia AI raised $15.5 million and built patented technology. But Dimitrios’s proudest milestone isn’t the capital—it’s reaching cash flow positive. “Right now, to some extent, R and D is funded by our customers.”

The discipline shows in his thinking: “I don’t feel like if we had a lot more money to throw into the commercial lens and would necessarily get better results. Sometimes it’s the opposite.”

Prove your go-to-market motion works before scaling it.

Lesson 7: Partner Selection Matters as Much as Product-Market Fit

Many founders treat fundraising as purely transactional. Dimitrios sees it differently: “It’s not just funds those people bring in. Actually it’s a marriage. Our investors are on our board and it’s great that we have those people on our board and we’re aligned on sentence and direction.”

His advice: “You have to know on a lot of doors, you have to look at many potential candidates and understand their goals, understand their values and make sure there is some alignment.”

This applies beyond investors to early customers, first hires, and advisors. Be as selective about your partners as you are about your product decisions.

The Through-Line

What ties these lessons together is patience and discipline in an ecosystem that rewards fast growth at any cost. Intelligencia AI built before selling. They listened before scaling. They reached cash flow positive before raising more.

For founders selling complex technology to conservative industries, speed isn’t always the answer. Sometimes the best go-to-market strategy is moving deliberately—building trust through proof, embedding in workflows, and proving unit economics before stepping on the gas.