Omen AI Acquires Aquatic Labs to Advance Real-Time Data Center Water Monitoring

Table of Contents

• You might want to know


• Main Topic


• Key Insights Table


• Afterwards...

You might want to know

• How could real-time water monitoring help data centers protect equipment while using less water?


• What does Omen AI’s acquisition of Aquatic Labs add to its technology and plans?

Main Topic

Data centers rely on water-based cooling to manage the heat generated by powerful computer chips. In the United States, data centers use 17 to 19 billion gallons of water each year to cool their chips, according to the Water Foundation. That figure is expected to triple in the next five years. As AI infrastructure expands, the scale of this demand presents both an operational challenge and a broader question about responsible water use.

Cooling systems need to be monitored to ensure that their fluids continue to work as intended. Yet conventional testing can involve collecting samples and sending them to a laboratory, with results taking multiple days. During that delay, a system problem—such as a failing valve or bacterial growth that could restrict water flow—may be difficult to identify quickly. Real-time sensing offers a way to provide operators with faster information about the condition of their cooling fluids.

Omen AI was founded in 2024 to address this monitoring gap. The company is developing sensors that can detect changes in water systems as they happen, helping operators identify potential faults and fluid-quality issues. Following a $31 million Series A in June, Omen announced that it is acquiring Aquatic Labs in a $16 million cash-and-stock deal. The acquisition brings together two companies working on real-time water sensing.

The companies’ technologies measure different properties. Omen’s sensors look for elements present in water, while Aquatic Labs’ sensor measures alkalinity. These approaches are complementary: combining them could give operators a broader understanding of the fluid than either sensor provides alone. Aquatic Labs CEO Allan Adams described the result as a “much richer picture of the water and the fluid” in remarks to TechCrunch. The companies also share an aim of replacing slow, manual testing with an automated process.

The companies came together after Omen founder Zach Laberge was introduced to Adams by an investor in the filtration industry. Their backgrounds reflect different paths into the same technical problem. Laberge left high school to pursue his first company, which performed similar fluid analysis for large construction machines that rely on hydraulic systems. Adams, by contrast, trained as a physicist and worked on advanced ocean-sensing technology. His research career included time as an MIT professor and as a researcher at the Woods Hole Oceanographic Institute before he founded Aquatic Labs.

Adams is joining the combined company as chief science officer. The teams are working to integrate the two technologies into a single sensor, which they expect to have on the market by early next year. Bringing the measurements together could make it easier for customers to assess fluid conditions through one monitoring system, though the product still needs to be integrated and brought to market.

Omen’s initial sensors are aimed at data center chips drawing 250 to 300 MW of power by the end of the year. Laberge told TechCrunch that this equipment represents about $5 to $7 billion in value. The company hopes its sensors will be installed on the equivalent of 1 GW of chips by the end of 2027. These figures indicate the scale of the infrastructure Omen is targeting, while also showing how its rollout depends on the continued construction and operation of high-capacity data centers.

The potential benefit is not limited to measuring water for its own sake. Fluid problems can put expensive computing equipment at risk. When a cooling system’s condition becomes uncertain, operators may choose to discard its water rather than risk damage. The fluid system then has to be restored, and operations may need to pause while that work takes place. Both the disposal and interruption can be costly.

More frequent, real-time information could help operators keep using the same fluid for longer when conditions remain suitable. It may also help them identify when intervention is needed before a problem escalates. The core value proposition is improved visibility: operators can make decisions based on timely measurements instead of relying only on delayed laboratory results or precautionary fluid replacement. The technology does not eliminate the need for maintenance or responsible water treatment, but it could support more informed decisions about both.

Adams also sees potential for water monitoring beyond the data center itself. Water enters these facilities, circulates through their systems, and eventually may be discharged into municipal water infrastructure. In comments to TechCrunch, he emphasized that the whole process should be managed safely and responsibly, and that doing so requires measurement. Monitoring could therefore become relevant not only to cooling performance, but also to how water is handled before and after it passes through a facility.

The acquisition comes amid debate about the scale of investment in AI infrastructure. AI companies have estimated that as much as $4 trillion could be spent on AI infrastructure by 2030. Some investors have become more skeptical about the pace and financial returns of the buildout, and hyperscaler stocks have fallen sharply in recent days. These shifts create uncertainty for companies whose prospects depend on new construction.

Laberge said Omen is less exposed to changes in sentiment about projects that have not yet begun because its customers are working on facilities being built today or already completed. He noted that those projects were financed 12 months ago. In his view, even if the market were cut in half, it would remain the biggest market in human history. That is the company’s perspective rather than a guarantee of future demand, but it explains why Omen believes its work can continue amid changing investor expectations.

Ultimately, the deal joins two forms of measurement and two distinct areas of expertise around a practical infrastructure need. Data centers require reliable cooling; operators need timely information about the water and fluids that support it; and the environmental implications of water use extend beyond the facility. Whether the combined sensor meets these ambitions will depend on successful technical integration, customer adoption, and the ability to deliver useful readings in demanding operating conditions.

Key Insights Table

Afterwards...

Further progress in data center water management will depend on more than combining sensors. Operators, researchers, and equipment providers will need to determine how real-time readings can be translated into reliable maintenance decisions across different cooling systems. This includes studying how sensors perform over time, how they detect relevant changes, and how their measurements can be incorporated into existing operational procedures.

There is also room to explore how monitoring can support responsible water use across the full facility lifecycle. Better measurement may help operators understand water quality at intake, within cooling systems, and at discharge. Continued work on water treatment, reuse, and discharge practices could complement sensing technology, while coordination with municipal water systems may help address impacts beyond data center boundaries.

As AI infrastructure develops, decision-makers will need to assess both computing capacity and the resources required to sustain it. A useful direction for future research is connecting operational data with practical water-efficiency measures, so that reliability, equipment protection, and responsible water stewardship can be considered together. The combined Omen and Aquatic Labs effort reflects one approach to this challenge: replacing delayed, limited testing with more continuous information. Its eventual impact will become clearer as the sensor is integrated, deployed, and evaluated in real-world facilities.