Omen AI buys Aquatic Labs for $16 million to watch data center water

Omen AI is acquiring rival sensor startup Aquatic Labs in a $16 million cash-and-stock deal, betting that real-time water monitoring becomes essential infrastructure for AI data centers. The deal, announced after Omen's $31 million Series A in June, pairs two founders with sharply different backgrounds around one shared thesis: cooling fluid is now too expensive — and too politically charged — to test the slow way.

The stakes are large and measurable. US data centers consume 17 to 19 billion gallons of water per year to cool their hot-running chips, according to the Water Foundation, and that figure is expected to triple within five years. For investors pouring billions into AI infrastructure, water use is both a cost line and a growing political liability.

Why cooling-fluid monitoring became a business

Data centers currently monitor their cooling water by sending fluid samples to external laboratories, a process that takes multiple days to return results. In the interim, operators fly blind on problems that develop fast: failing valves, or bacterial growth thick enough to choke off water flow inside the system.

Omen AI was founded in 2024 to replace that cycle with real-time sensing. The company's sensors detect elements present in the water, flagging chemical conditions as they develop rather than days after the fact. Aquatic Labs, the company it is now absorbing, built a complementary instrument: a real-time sensor that tests the water's alkalinity (its acid-base balance, a key indicator of fluid health).

The two technologies fit together naturally, which is what made the acquisition attractive. "The combination unites" the two approaches into a single device, producing a "much richer picture of the water and the fluid," Aquatic Labs CEO Allan Adams told TechCrunch. He added that the deal also unites the two companies' vision of automating a process that had previously been slow and manual.

The acquisition originated in an introduction. An investor in the filtration space put Omen founder Zach Laberge in touch with Adams, and the founders discovered their startups were attacking the same problem from different angles.

Two founders, two paths to the same sensor

The merged company combines two archetypal founder profiles. Laberge dropped out of college to build his first company, which performed similar fluid analysis for large construction machines that depend on hydraulics. Adams is the academic counterpart: a trained physicist who spent much of his career developing advanced ocean sensing technology as an MIT professor and Woods Hole Oceanographic Institute researcher before starting his company.

Adams now takes the role of chief science officer at the combined company. His remit is the science of measurement; Laberge's is the business built on top of it.

The integration work is already underway. The combined teams are merging both sensing technologies into a single device, which they expect to bring to market by early next year. That timeline is aggressive for a hardware merger, and the source does not specify how the two detection methods will be physically unified in one unit.

What are the actual deployment numbers?

Omen's existing sensors will monitor chips drawing 250 to 300 MW of power by the end of this year, Laberge told TechCrunch. He valued that compute at roughly $5 to $7 billion. The company's stated target is installation capacity equivalent to 1 GW of chips by the end of 2027.

Those numbers describe the hardware under watch, not Omen's revenue, and the source provides no sales figures, customer names, or contract values. The company also does not disclose pricing for the combined sensor, leaving its commercial model unspecified.

The economic pitch rests on uptime and fluid longevity. When a cooling system drifts out of specification, data center operators typically choose to dump the water rather than risk damage to expensive equipment. That forces a shutdown until the fluid system is restored — a costly interruption for facilities running around the clock. Continuous monitoring lets operators use the same fluid for longer and reduces the cost of cleanup when something does go wrong.

Can the market downturn reach them?

The acquisition lands during a turbulent stretch for AI infrastructure sentiment. AI companies once estimated that as much as $4 trillion would be spent on AI infrastructure by 2030, but some investors have grown skeptical of the buildout, and hyperscaler stocks have fallen sharply in recent days.

Omen's team argues it is insulated from that volatility because its work begins after a data center exists, not before. "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," Laberge said.

He added a broader hedge: "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."

That confidence assumes operators keep prioritizing fluid management even under capital pressure — a plausible but untested claim, since the source offers no customer retention or backlog data to back it.

Beyond the data center

Adams frames the combined technology's potential reach as wider than server halls. "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," he told TechCrunch.

That argument ties Omen's sensors to a regulatory question, not just an operational one: as data center water consumption triples, what flows back into municipal systems will attract scrutiny, and measurement is the precondition for any accountability. No regulations or partnerships are named in the source, so that ambition remains a direction rather than a plan.

The next hard checkpoint is the combined sensor's launch by early next year, followed by the 1 GW installation target at the end of 2027 — two dates against which the merged company's execution can now be measured.