BU BÖLÜM HAKKINDA
Our guest in this episode is Kyle Hanslovan, Co-Founder and CEO of Huntress. When Kyle started Huntress in 2015, most investors believed protecting small and mid-sized businesses wasn't a venture-scale opportunity. The contracts were too small, customer churn would be too high, and the market simply wasn't attractive enough. Kyle heard “no” more than 60 times from VCs before raising his first institutional round.
Ten years later, Huntress has just crossed $250M ARR, protects more than 270,000 businesses, and has become one of the defining cybersecurity companies serving the 99% of organizations that don’t have dedicated security teams. Even more remarkably, Huntress achieved this growth without abandoning its original mission or moving upmarket.
On Inside the Network, Kyle shares the unconventional story behind building one of cybersecurity's fastest-growing companies. We discuss why he ignored investor advice, why customer revenue mattered more than venture funding, how Huntress built a partner-first go-to-market strategy that became a lasting competitive advantage, and why serving the SMB market turned out to be a much bigger opportunity than most people realized.
We also dive deep into AI and what it means to build an AI-centric cybersecurity company. Kyle explains why Huntress didn't start as an AI-native business, how years of automation and data science laid the groundwork for adopting modern AI, where large language models are genuinely changing security operations, and why he believes technical founders with deep research DNA will have a significant advantage in the AI era.
Finally, Kyle shares candid lessons about leadership, founder psychology, and the personal cost of building venture-scale companies. He reflects on growing up “pretty darn broke,” what drove him to become an entrepreneur, why founders often underestimate the sacrifices required to build enduring businesses, and how he has learned to balance relentless ambition with building a company around a mission larger than himself.
