Intelligencia AI’s Pivot: From McKinsey Venture to Venture-Backed Startup
Picture the ideal corporate innovation setup: You’re at McKinsey building an AI vertical for pharmaceutical R&D. You have data scientists, software engineers, and the McKinsey brand opening doors.
Then you walk away from it all to bootstrap in a shoebox apartment where your first hire sleeps on your sofa.
In a recent episode of Category Visionaries, Dimitrios Skaltsas, CEO and Co-Founder of Intelligencia AI, shared the story of that pivot.
“It’s like being in love, like falling in love where everything is rosy and you’re very optimistic, and somehow you have a big disregard for risk, which helps a lot,” Dimitrios says. But also: “Very creative days and, you know, also challenging days or very scrappy days.”
Here’s what actually happens when you trade corporate resources for founder freedom.
The McKinsey Moment: Building Something You Can’t Keep
The setup was exceptional. This was 2015-2016, the early days of AI.
“McKinsey was experimenting with big data and AI, and they had what they call new ventures. And at some point, I did not want to do consulting anymore. And I was offered the opportunity to move into ventures and actually build the vertical for pharmaceutical RD, both track discovery and track development,” Dimitrios recalls.
He built a team of data scientists and software engineers. He had conversations with pharma about what could be done better with AI. One of those ideas became Intelligencia AI’s core.
But there was a problem: “McKinsey. We didn’t have institutional patients or risk appetite work on this.”
This is the moment many in corporate innovation face: You’ve validated something, but the institution has constraints. Summer to fall 2017, Dimitrios left McKinsey and started licensing the AI technology.
The Reality Check: Sofa Beds and Savings
Dimitrios doesn’t romanticize the struggle.
“Our sheriff, data science, who was the first person to join the company beyond me, and my Co-Founder. She literally used to sleep on my sofa in a shoebox apartment in New York.”
The financial pressure was real. “We didn’t have any source of income as a company. We were literally bootstrapping the whole thing. And I was digging into my savings.”
Coming from McKinsey, he’d built a comfortable life. Now he was watching his savings decrease month after month, hoping the math worked before the money ran out.
The Falling in Love Metaphor (And What Comes After)
Dimitrios keeps returning to the metaphor of falling in love when describing those first six months. It captures both the irrational optimism that makes you do crazy things and the intensity that makes you feel alive.
“Sometimes I make the metaphor of it’s like being in love, like falling in love where everything is rosy and you’re very optimistic, and somehow you have a big disregard for risk, which helps a lot.”
That “big disregard for risk” is the psychological state that lets you make decisions that look insane from the outside. “Everything is possible and, you know, let’s create something, let’s append the world.”
But he extends the metaphor: “Back to the metaphor of falling in love. At some point it feels like, okay, now, you delivered the baby, and suddenly you have responsibilities, and you know that the baby stays up at night and poops and gets sick, and you have to take care of it.”
This is the transition every founder goes through: from the excitement of creation to the weight of responsibility.
The Product-First Gamble
Dimitrios’s McKinsey background influenced a crucial decision that most lean startup advocates would say was wrong.
Instead of talking to customers and selling before building, they went product-first. “We started product first, and for many years, actually, we have retained that money, but we built something.”
They launched in fall 2017 and spent months building. No customer conversations. Just heads-down building. “We had the first results in sometime late spring 2018. And I was like, wow, we solved the problem, right?”
This was strategic: In pharma, you can’t sell on promises. You need proof first. But nine months of building with no revenue while your savings drain is terrifying.
What Made It Work: Maintaining Early Day Energy
With Intelligencia AI having raised $15.5 million and reached cash flow positive, Dimitrios is clear about what he’d preserve.
“I never looked back. So I think we did the right thing. I would love to relieve those days.”
But rather than just nostalgia, he maintains elements of that energy: “What I often do is I try to relive it by maintaining some of the elements, some of these early day elements and culture in the company.”
The real skill isn’t just surviving the early days, but extracting the cultural elements that made them special.
The Principle: When to Leave vs. When to Stay
Dimitrios’s story isn’t “always quit your job to start a company.” It’s understanding when the institution you’re in can’t support what you need to build.
McKinsey gave him access to pharma companies, data science talent, and space to explore. That was invaluable for understanding the problem.
But when it came time to build a product company—to commit years to developing patented technology—McKinsey’s model couldn’t support it. “We didn’t have institutional patients or risk appetite work on this.”
The decision point isn’t “do I want to be a founder?” It’s “can what I need to build exist inside this institution?”
The Evolution from Butterflies to Babies
What’s changed for Dimitrios isn’t the excitement—it’s the nature of the challenge.
“You have to reinvent yourself, which means it never gets boring. The shift is that, again, back to the metaphor of falling in love. At some point it feels like, okay, now, you delivered the baby, and suddenly you have responsibilities.”
The company has customers, revenue, and is cash flow positive. “What changes over time for me is the sense of responsibility, and that’s limiting in many ways, but it helps people mature, and that’s a good thing.”
This is the trade every successful founder makes: You trade pure creative freedom for the satisfaction of building something that matters, that lasts, that employs people and serves customers.
The butterflies don’t go away. They become something deeper—commitment.
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