While much of the AI spotlight shines on Silicon Valley giants and well-funded startups, a quiet revolution is happening in America’s heartland. Chicago-based Introl has emerged as one of the fastest-growing companies in the AI infrastructure space, proving that strategic positioning and operational excellence can outperform even the best-funded competitors.
The company’s remarkable ascent comes amid unprecedented demand for GPU deployment services as organizations race to build computational capacity for AI workloads. Founded in 2021 by Ryan Puckett, Introl has grown annual revenue by nearly 10,000 percent over three years, reaching approximately $38 million in domestic revenue last year alone. This explosive growth trajectory demonstrates how infrastructure providers are becoming the unsung heroes of the AI revolution.
What makes Introl’s story particularly compelling is its bootstrapped origins. Unlike many AI infrastructure companies that have relied on massive venture capital injections, Puckett built the company through careful cash flow management and, initially, “a lot of credit card debt.” This approach has allowed Introl to maintain control while scaling rapidly to meet market demands.
The GPU Deployment Specialist
Introl specializes in what industry insiders call “rack and stack” operations – designing and implementing the physical infrastructure needed to connect GPUs in data centers. According to CTO Blake Crosley, the company has deployed “up to 100,000 GPU units in a data center,” with each installation requiring extensive fiber optic cabling. The company has run more than 40,000 miles of fiber optic cable to date.
“We don’t actually own or operate the data centers,” Crosley explains. “We basically help design, like, what does it look like to actually get that set up in the space? Once the racks are in place, how are we going to actually connect everything together?”
This specialized work requires both technical expertise and massive logistical coordination. The company maintains around 45 to 50 full-time employees but leverages over 1,000 subcontractors to handle installations across global data centers. These facilities are so massive that workers use golf carts to navigate them, and their footprints are often measured by how many Costco stores could fit inside.
Operational Challenges in the AI Boom
The breakneck pace of AI adoption creates significant operational hurdles. Puckett identifies speed to market as his biggest challenge, noting that clients sometimes provide barely a week’s notice to deploy teams to data center locations.
“In a lot of cases, because they are trying to get things online so quickly…certain specific sections of [the data centers] are being built while you’re in a different part,” Puckett describes. “It’s a constant flow of trucks coming in, dropping off pallets of cables.”
The logistical complexity extends beyond the data centers themselves. Finding accommodation for hundreds of staff members in small towns where data centers are typically located presents another layer of challenge, highlighting the broader infrastructure strains created by the AI investment boom.
Strategic Positioning Beyond Silicon Valley
Puckett’s decision to base Introl in Chicago reflects a strategic vision that diverges from the typical tech narrative. “There’s not a better city in the country,” he says. “There was no other thought in my mind to build it anywhere else.”
This Midwest location provides access to talent and resources outside the competitive and expensive Bay Area ecosystem. The approach mirrors other successful technology ventures that have found advantage in unconventional locations, much like innovative teams building outside traditional tech hubs.
Introl’s success also highlights the growing importance of diverse leadership in technology infrastructure. As the industry evolves, companies that embrace varied perspectives are positioning themselves for sustainable growth, similar to how women are increasingly leading data center innovation.
Navigating the AI Bubble Conversation
With concerns about potential AI market corrections, Introl’s leadership remains pragmatic about the future. “Obviously there’s a lot of talk about [an] AI bubble and stuff like that,” acknowledges Crosley. “The players are huge, and the money that’s flowing is even bigger. But from a user perspective, on the side of utilizing AI, I can only see things expanding faster in the total adoption and usage.”
Puckett admits uncertainty about how the company would pivot if GPU deployments “fell off the face of the earth,” though maintenance of existing installations could provide a potential pathway. Currently, about 70 percent of Introl’s work involves new installations, while 30 percent focuses on maintaining pre-existing sites.
The company’s bootstrapped approach and focus on fundamental infrastructure needs position it well to weather market fluctuations. This resilience strategy shares similarities with investment firms that succeed by defying conventional VC wisdom through disciplined capital allocation and operational focus.
The Future of AI Infrastructure
Introl’s story represents a broader shift in how technology infrastructure gets built and deployed. As AI becomes increasingly integral to business operations worldwide, the companies that provide the foundational elements – the GPUs, connectivity, and physical infrastructure – may prove more durable than the applications built on top of them.
The company’s rapid growth from freelance project management to deploying hundreds of thousands of GPUs demonstrates that in the AI gold rush, the pickaxe sellers aren’t just facilitating the revolution – they’re building its very foundation. And they’re doing it from places like Chicago, far from the spotlight but essential to the technology’s future.
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