The Story of Zenlytic: Building the Future of AI-Powered Business Intelligence

Explore how Zenlytic evolved from a data science consultancy to pioneering AI-powered business intelligence, and learn how they’re reshaping the future of data analytics for mid-market companies.

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The Story of Zenlytic: Building the Future of AI-Powered Business Intelligence

The Story of Zenlytic: Building the Future of AI-Powered Business Intelligence

Sometimes the most compelling business opportunities emerge from the intersection of parallel developments. In a recent episode of Category Visionaries, Ryan Janssen shared how Zenlytic’s journey began at precisely such a crossroads.

The Origins: When Two Streams Converged

While pursuing their master’s degrees in machine learning and data science, Ryan and his co-founder found themselves witnessing two simultaneous revolutions. The first was technological: they were present for the birth of transformer models, which would eventually power today’s AI revolution. “The famous paper, Attention is All You Need, which kind of underpins the development of the transformer, which is what is the operating unit of every sort of large language model today that came out while we were studying together,” Ryan recalls.

The second revolution was happening in the business world. Through their data science consultancy, they observed firsthand how companies struggled to utilize their expanding data resources effectively. This unique vantage point revealed a critical gap in the market.

From Consultation to Innovation

Their consulting experience provided crucial insights into how businesses actually used (or failed to use) their data. “When you’re a big nerd like me, and you’re good at Python or SQL or whatever, it was remarkable how fast we could actually go from cold to the most well-informed person in the room by just doing a couple of hours of data exploration as consultants,” Ryan explains. However, this efficiency highlighted a bigger problem: most business users lacked the technical skills to achieve similar results.

The AI Revolution Accelerates

While Zenlytic had been incorporating AI capabilities from early on, the release of ChatGPT in December 2022 marked a turning point. “Within an hour of that coming out, we just seen the capabilities of that tech, and we said, okay, it’s time to accelerate and double down on this,” Ryan shares.

But unlike many companies rushing to capitalize on the AI trend, Zenlytic’s approach remained grounded in solving real business problems. They focused on creating an AI-powered data analyst that could provide instant, reliable insights while maintaining the accuracy that businesses require.

Building for the Mid-Market

Zenlytic made a strategic decision to focus on mid-market companies, identifying a sweet spot where their solution could provide the most value. “We like the mid market sales cycles versus long enterprise sales cycles… the sweet spot for us is something like our customers mostly have revenues between sort of 15 and $500 million a year,” Ryan explains.

The Vision Ahead

Looking to the future, Ryan sees Zenlytic as the next evolution in business intelligence platforms. He traces the industry’s development through previous innovations: “Ten years ago or whatever, there’s Tableau. And Tableau was the first person to really crush building great dashboards… After that came Looker. Looker was the first tool to really popularize the semantic layer in modern history.”

Now, with the emergence of powerful language models, Zenlytic aims to pioneer the next wave of business intelligence tools. Their vision goes beyond simply adding AI capabilities to existing solutions – they’re reimagining how businesses interact with their data through natural language interfaces.

The pace of change in AI technology continues to accelerate, creating both opportunities and challenges. As Ryan notes, “The pace of this change is like nothing I’ve ever seen… We’re seeing stuff happen day by day with AI.” In this rapidly evolving landscape, Zenlytic’s commitment to solving fundamental business problems while leveraging cutting-edge technology positions them to play a crucial role in shaping the future of business intelligence.

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