Omen AI raises $31M to solve a growing data center problem: bacteria in liquid cooling

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Omen AI raises $31M to solve a growing data center problem: bacteria in liquid cooling

As demand for AI compute power surges, data center operators are pushing their hardware harder than ever. One consequence of that intensity is a growing problem with the liquid used to cool high-performance chips: bacterial outbreaks.

Liquid cooling systems rely on a carefully balanced mixture of water and biocides to prevent microbial growth. To improve heat absorption, operators sometimes increase the water ratio, but that also creates a more hospitable environment for bacteria. The result can be clogged cooling lines, degraded performance, and costly system shutdowns that can last five or six hours — downtime that can cost millions of dollars in lost compute capacity.

A real-time solution for a hidden problem

Omen AI, a startup founded in 2024, has developed a tiny spectrometer that monitors the chemical health of cooling fluid in real time. The device can detect early signs of bacterial contamination, as well as wear particles like copper or chromium from pumps and silicon from seals, before they cause system failures.

“You’re not risking huge amounts of downtime because you have no insight into what’s going on chemically,” said Zach Laberge, CEO and founder of Omen AI, in an interview.

Today, Omen AI announced it has raised a $31 million Series A round led by Nava Ventures, with participation from CRV, Vanderbilt University, Mann+Hummel, Starhill Holdings, Hard Launch Capital, and personal investments from executives at Bridgestone, GM, Johnson Controls, and TensorWave. The company has raised $40 million since its founding.

From construction equipment to data centers

Laberge’s path to data center monitoring is an unconventional one. He founded his first company at age 14, raising $3 million to install sensors on construction equipment, before dropping out of high school with the support of his parents. After that startup shut down, he launched Omen in 2024 with a focus on fluid systems for heavy machinery.

The idea was to replace the time-consuming process of extracting fluid samples and sending them to a lab with real-time awareness. Caterpillar dealerships became early customers for Omen’s heavy vehicle monitoring. But Caterpillar is also a major supplier of gas-powered turbines and generators for data centers, and it didn’t take long for Omen to spot a bigger opportunity.

“That was kind of the transition,” Laberge said. About six months ago, “a lot of the dealerships were saying, ‘Hey, we’re starting to put sensors on our turbines, can you guys do anything on the building side of things?’” Omen discovered that those buildings are full of fluid, from HVAC systems to chip cooling.

Why this matters for AI infrastructure

The timing of Omen’s pivot is significant. The AI boom has driven unprecedented demand for compute power, and data center operators are under pressure to maximize utilization of every GPU rack. Liquid cooling is becoming more common as chip densities increase, but managing the fluid quality has remained a blind spot for many operators.

“It’s rare to see such a young founder who has the respect of established, large corporations in a space that moves a bit more slowly,” said Cory Rellas, a partner at Nava Ventures who sits on Omen’s board. “For Omen in particular, much of our diligence came through our introductions with large customers which quickly validated their approach.”

Omen is already working with a dozen data center customers, including TensorWave, a company building an AI compute cloud on AMD chips. “The fluid running through these massive systems is a critical variable that most of the industry is flying blind on,” said Piotr Tomasik, TensorWave’s president, in a statement. “Omen sees the future of infrastructure exactly the way we do, better monitoring to optimally support compute customers.”

Competition and technological edge

While many organizations still rely on mailing fluid samples to labs for analysis, Omen is not alone in developing on-premises analytics. Pyxis, an established water-monitoring firm, rolled out its own data center coolant monitoring product earlier this month.

The key technological advances that have enabled this approach, according to Laberge, are recent improvements in both optical technologies and signal processing software. “Hardware is just cheap enough that it makes sense to play at scale, and then signal processing lets us make more sense out of the noise,” he said.

Conclusion

Omen AI’s approach addresses a growing operational pain point for data center operators as they scale AI infrastructure. By providing real-time visibility into fluid health, the company aims to reduce costly downtime and improve the reliability of liquid cooling systems. The $31 million Series A round positions Omen to expand its data center business while continuing to serve its original heavy equipment customers.

FAQs

Q1: What problem does Omen AI solve for data centers?
Omen AI monitors the chemical health of liquid cooling fluid in real time, detecting bacterial contamination and equipment wear before they cause system failures or costly downtime.

Q2: How much funding has Omen AI raised?
Omen AI has raised $40 million since its founding in 2024, including a $31 million Series A round announced today led by Nava Ventures.

Q3: Who are Omen AI’s main customers?
Omen works with Caterpillar dealerships for heavy equipment monitoring and is now expanding to data center customers, including TensorWave, an AI compute cloud provider using AMD chips.

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