Guest: Rob Hirschfeld (LinkedIn)
Company: RackN
Show Name: An Eye on AI
Topic: AI Infrastructure

AI may be reshaping software, but behind the scenes, it’s also transforming infrastructure. In this clip, Rob Hirschfeld, CEO and Co-Founder of RackN, outlines RackN’s mission to make AI infrastructure more accessible, automated, and sustainable for organizations everywhere.

According to Hirschfeld, RackN is already helping enterprises accelerate how they deploy and manage AI systems. Through its Digital Rebar automation platform, the company has helped customers slash provisioning and reset times while improving energy efficiency and reducing idle capacity. The same principles that revolutionized enterprise operations — automation, repeatability, and consistency — are now being applied to AI data centers.

“AI infrastructure is incredibly expensive and complex,” says Hirschfeld. “Many teams spend weeks patching and onboarding systems. We’re helping them bring those enterprise-grade operational practices into the AI space.”

At the heart of this transformation is a broader goal: democratizing AI infrastructure. Hirschfeld predicts that AI will move beyond hyperscalers and frontier labs into mainstream enterprises — companies that need to train or deploy models for edge use cases, internal automation, or data sovereignty. “We believe very passionately that AI will be democratized,” he says. “Companies will be running their own models — they need to, whether it’s for cost, compliance, or control.”

RackN’s automation technology plays a critical role in this shift. By reducing the friction of setup, configuration, and ongoing maintenance, organizations can move faster, spend less, and scale smarter. The payoff isn’t just efficiency — it’s accessibility. Smaller companies and enterprises outside the tech giants can finally manage their own AI infrastructure with the same reliability and speed once reserved for cloud providers.

Hirschfeld also touches on the broader impact of AI-driven infrastructure automation: energy efficiency. When clusters are turned around faster, they spend less time idle, reducing wasted power and cooling overhead. It’s a subtle but significant step toward more sustainable AI operations.

The bigger vision is clear. RackN isn’t just building tools — it’s creating a framework for the future of infrastructure ownership. By combining automation with open, adaptable design, RackN aims to empower organizations everywhere to control their infrastructure destiny — whether that’s in the cloud, at the edge, or on-prem.

As Hirschfeld puts it, “AI is just the beginning. Our mission is to make infrastructure ownership and management accessible to everybody.”