5 Go-to-Market Lessons from DeepSet’s Journey in Building AI Infrastructure
When most founders talk about building AI companies, they focus on the technology. But in a recent episode of Category Visionaries, DeepSet founder Malte Pietsch revealed how early market skepticism shaped their unconventional go-to-market approach, offering valuable lessons for technical founders navigating similar challenges.
- Use Services to Build Deep Market Understanding Rather than raising venture capital immediately, DeepSet started with just €5,000 and built a profitable services business. “We started basically doing professional services. We built custom AI solutions, learning solutions for enterprise customers,” Malte explains. This approach provided crucial market insights before they had a product.
The key lesson wasn’t just about bootstrapping – it was about using services as a learning laboratory. “Be close to your customers. So I think for us, this bootstrapping phase was incredibly valuable because we just learned so much about really pain points of these customers in various companies before we had anything.”
- Create Developer Advocacy Through Open Source DeepSet’s distinctive “sandwich motion” strategy uses open-source software to build credibility with technical teams while selling to business decision-makers. “It’s really a lot of developers out there know it, tried it, like it and typically like the devs are not our buyers,” Malte notes. “They don’t swipe the credit card and pay the check for this commercial platform, but they help a lot in this buying process.”
This creates powerful internal champions during enterprise sales cycles: “At some point, of course they ask the developers about hey, what is that technology? Does it make sense? Do you trust us.”
- Prioritize Production Value Over Demo Hype In the post-ChatGPT era, DeepSet maintained focus on production deployment rather than chasing trends. “Last year, I think that was where a lot of this noise happened, where so much new things became possible. So a lot of cool ideas, great ideas, exciting demos,” Malte reflects. “But I think at some point, if you don’t want to become hype and just a bubble, you need to show the value coming out of things.”
- Time Your Sales Organization Transition One of Malte’s most candid insights relates to building their sales function: “I would probably also hire a sales team earlier, to be honest. So we did, I think, for a very long time, Founder led sales and only hired last October.” This highlights the delicate balance between maintaining founder-led customer development and building scalable sales processes.
- Avoid the Technology Trap Perhaps most importantly for technical founders, Malte warns against over-focusing on technology at the expense of market understanding: “It’s very risky if you are a tech company, if you build a very deep tech product that you may sometimes focus too long on just the technology because you have this vision, you have this idea, you just need to build it, but then maybe you hit the market too late.”
The Power of Strategic Patience DeepSet’s journey challenges conventional wisdom about building AI companies. While many founders rush to capitalize on market hype, their story suggests that sometimes the best way to build in a hot market is to take a methodical approach focused on deep customer understanding.
“We always had this conviction,” Malte reflects on their early days. “We had very strong beliefs from day one that it’s so obvious to us that at some point you would talk with machines, you will rather chat with products.” But rather than chase that vision directly, they built foundational understanding through services, created community through open source, and focused relentlessly on production value.
For technical founders building in emerging markets, DeepSet’s journey offers a powerful reminder: sometimes the path to building innovative technology products requires strategic patience and indirect routes to market. Their success suggests that in the race to build the future, the tortoise strategy – building deliberately based on deep customer understanding – might ultimately outpace the hares chasing the latest trends.