Omen AI buys Aquatic Labs for $16M

Data centers devour water to keep their chips from overheating, and most operators still learn about problems in that water days after the fact — by mailing samples to a lab. A small startup called Omen AI, founded in 2024, has built a real-time sensor meant to replace that lag, and it is now buying a competitor to widen what a single probe can detect.

Omen is acquiring Aquatic Labs in a $16 million cash-and-stock deal, the company told TechCrunch. The move follows a $31 million Series A in June, and it folds a second sensing approach into Omen's hardware rather than leaving the two firms to compete for the same racks.

The timing matters because water use is becoming a harder number for data center builders to defend. According to the Water Foundation, US data centers consume 17 to 19 billion gallons of water annually for cooling, and that figure is projected to triple within five years.

Two sensors, one probe

The two companies were working on related but distinct problems. Omen's sensors look for specific elements present in cooling water, while Aquatic Labs' device measures alkalinity. Neither alone gives an operator a complete read on whether the fluid loop is healthy.

Combining them into one sensor produces a fuller account of conditions inside the loop, Aquatic Labs CEO Allan Adams said in an interview with TechCrunch.

"much richer picture of the water and the fluid"

— Allan Adams, CEO of Aquatic Labs

The pairing also aligns the two firms around a shared goal: automating a process that has traditionally required off-site lab work and multi-day waits before anyone knows whether something in the loop has gone wrong.

What the sensors watch for

The failure modes Omen is targeting are practical ones. A valve can begin to fail, changing the flow through part of the system. Bacteria can multiply in the water and start to choke off circulation. Either problem, left undetected, threatens the equipment the loop exists to protect.

Current practice gives operators little warning. Samples are drawn and shipped to a laboratory, and results come back days later — long after a small deviation has had time to become a larger one. Omen's pitch is that continuous, on-site measurement closes that gap.

Aquatic Labs brings the alkalinity measurement into the same package. According to the companies, putting both readings in a single sensor lets operators see the state of the fluid as a combined picture rather than as separate test results interpreted in isolation.

The dropout and the oceanographer

The deal pairs two founders with little in common on paper. Omen founder Zach Laberge left high school to start his first company, which performed fluid analysis for large construction machines that rely on hydraulics. Adams came from academia: trained as a physicist, he spent much of his career building advanced ocean sensing technology as an MIT professor and a researcher at the Woods Hole Oceanographic Institute before founding Aquatic Labs.

The introduction came through an investor in the filtration space, who connected Laberge and Adams. That conversation led to the acquisition rather than a partnership or a licensing arrangement.

Adams is staying on as the combined company's chief science officer. The two teams are now working to merge their technologies into one sensor, which they expect to bring to market by early next year.

The water bill behind the buildout

Cooling is one of the less visible costs of running AI workloads, but it is a substantial one. The Water Foundation's estimate of 17 to 19 billion gallons a year for US data centers reflects how much fluid the sector moves to keep hot-running chips within operating limits — and the projection that the figure will triple over the next five years suggests the problem grows with every new facility.

For investors funding AI infrastructure, that is both an expense and a political liability. Omen's argument is that better measurement reduces how much water has to be consumed and discharged in the first place.

Adams said he wants the combined technology to be useful beyond the data center fence line as well.

"water goes into data centers, and then it comes out and gets dumped into municipal water, and you want that whole process to happen in a way that's as safe and responsible as possible — and that means you got to measure stuff."

— Allan Adams, CEO of Aquatic Labs

Uptime is the selling point

The commercial case rests on what happens when a fluid system drifts out of specification. Operators typically choose to dump the water rather than risk damage to expensive equipment, which means shutting down operations until the fluid system is restored. That downtime carries a significant cost.

Continuous monitoring lets operators keep the same fluid in service longer and limits the expense of cleaning up after a problem. In a facility where the chips themselves represent enormous capital outlay, avoiding an unnecessary shutdown is the value proposition.

Omen's sensors will initially be monitoring chips drawing 250 to 300 MW of power by the end of the year, a footprint Laberge valued at roughly $5 to $7 billion. The company's stated goal is to be installed on the equivalent of 1 GW of chips by the end of 2027.

A spending slowdown that skips the post-build phase

AI companies once estimated that as much as $4 trillion would be spent on AI infrastructure by 2030. Some investors have since grown skeptical of the buildout, and hyperscaler stocks fell sharply in recent days.

Laberge said the shift in sentiment does not change Omen's position, because its work begins after a data center has already been constructed.

"We're working customers on stuff they're building today or have already built, and so it doesn't really affect us because all of those projects were financed 12 months ago"

— Zach Laberge, founder of Omen AI

He added that even a reduced market would remain very large.

"Our view is, if there's tightness, this is still going to be the biggest market in human history, even if you sliced it in half."

— Zach Laberge, founder of Omen AI

The numbers behind the deal

• $16 million — purchase price for Aquatic Labs, in cash and stock
• $31 million — Omen AI's Series A, raised in June
• 17 to 19 billion gallons — annual US data center water use for cooling, per the Water Foundation
• Triple — projected growth in that water use over the next five years
• 250 to 300 MW — power draw of chips Omen's initial sensors will monitor by year's end
• $5 to $7 billion — Laberge's valuation of that initial chip footprint
• 1 GW — equivalent chip capacity Omen hopes to serve by the end of 2027
• $4 trillion — earlier industry estimate for AI infrastructure spending by 2030

Why it matters

The deal is small next to the sums moving through AI infrastructure, but it points at a cost that does not appear on most chip roadmaps. Water for cooling is a recurring expense and a growing public-relations problem for operators, and the source of that expense is largely invisible until a lab report comes back or a loop fails.

If real-time sensing works as advertised, it could change the economics of running a facility — less water dumped, fewer unplanned shutdowns, and a measurable record of what leaves the site. That record may matter as much to regulators and surrounding communities as it does to the operators' finance teams, though the technology is only now heading to a combined commercial sensor expected early next year.

For the broader buildout, Omen's bet is that efficiency tooling sells regardless of whether spending on new facilities cools off, because the equipment already financed still has to run. Whether customers agree at the scale Laberge describes will be visible in installations over the next two years.