Omen AI Buys Aquatic Labs to Fix the Data Center Water Crisis
US data centers burn through billions of gallons of water each year to keep hot-running chips from melting.

US data centers burn through billions of gallons of water each year to keep hot-running chips from melting. That cooling bill is expected to triple in the next five years, creating a massive logistical bottleneck for an industry already sinking billions into AI infrastructure. Until now, checking the health of that cooling fluid meant sending off physical samples to a lab in a slow process that leaves multi-billion-dollar servers vulnerable to sudden valve failures or choking bacteria.
Omen AI is trying to speed that up by building real-time monitoring sensors. Fresh off a Series A funding round, the startup is buying competitor Aquatic Labs in a cash-and-stock deal. Omen’s sensors check for trace elements in the fluid, while Aquatic Labs tests alkalinity. Merging the two approaches gives operators a much richer picture of their cooling systems without waiting days for laboratory results.
Our read is that while investors grow squeamish over the multi-trillion-dollar AI buildout, companies supplying the plumbing are insulated from shifting market sentiment. Founder Zach Laberge notes that Omen targets data centers already built or actively under construction with capital secured months ago. By preventing catastrophic fluid degradation that forces operators to dump water and halt expensive operations, real-time monitoring turns a messy operational hazard into predictable maintenance.
With the former MIT professor and ocean sensing researcher Allan Adams stepping in as chief science officer, the combined team plans to launch an integrated sensor early next year.
That timeline puts their hardware directly in front of massive power loads coming online by the end of next year.
As data center footprints expand, watching the water may ultimately prove more critical than watching the code.
The story so far
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Original publication: 2 November 2026 20:30





