Omen AI acquires Aquatic Labs for $16 million: automating cooling chemistry to protect data centers

Omen AI has sealed a deal to acquire its rival Aquatic Labs for $16 million in cash and stock, shifting the data-center efficiency battle from visible power consumption to the invisible chemistry of cooling fluids. The transaction follows a few months after Omen raised $31 million in a first-round financing in June, combining two emerging technologies to address a silently worsening crisis at the heart of high-performance computing infrastructure. According to the Water Institute, data centers in the United States alone consume between 17 and 19 billion gallons of water each year to cool rapidly heating chips, a figure projected to triple within the next five years, turning cooling management into a growing financial burden and political pressure for investors.

The operational dilemma the deal aims to solve lies in the extreme slowness of cooling-fluid monitoring, as facilities traditionally rely on manually drawn samples sent to external labs in a process that takes several days. During that interval, valves may corrode or bacteria can proliferate inside pipes, threatening flow blockage and coolant shutdown.The operational risk usually drives operators to discard the fluids entirelyFearing damage to costly servers, which would halt computing and incur expensive re-cleaning and refilling costs, Omen was founded in 2024 to develop an instant sensor that detects chemical constituents, valve failures and bacterial growth, while Aquatic Labs created a parallel sensor that measures fluid alkalinity with precision. The two companies have begun integrating the technologies into a unified sensor slated for market launch early next year, offering a real-time, comprehensive readout of fluid health and extending its operational lifespan safely.

The alliance was brokered by an investor specialized in filtration, bringing together two distinct technical leadership backgrounds: Zak LaBerge, Omen’s founder, who left high school to launch his first venture analyzing fluids in massive hydraulic construction equipment, and Alan Adams, a former MIT physics professor and Woods Hole Oceanographic Institute researcher who led ocean-sensor development before founding Aquatic Labs and now serves as chief science officer of the merged entity. The company plans to deploy sensors monitoring chips that consume between 250 and 300 megawatts by the end of this year, valued at $5-7 billion, with a target of reaching monitoring equivalent to a full gigawatt of chips by the end of 2027. The technology’s ambition also extends beyond server walls, as cooling water eventually returns to public municipal networks, and continuous monitoring becomes an environmental and regulatory necessity to ensure safe discharge.

Despite recent volatility in the shares of major cloud-computing firms and rising Wall Street doubts about infrastructure expansion, spending on which is estimated to reach $4 trillion by 2030, Omen’s team expresses no concern about shifting investment sentiment. LaBerge attributes this confidence to the fact that the company’s projects are tied to data centers funded more than twelve months ago that are now under construction or already operational, asserting that this market will remain the largest in modern history even if it contracts to half its projected size.Continuing operation of existing facilities isolates maintenance services from stock speculationThis makes measurement devices a critical element for reducing waste and ensuring maximum readiness for every invested watt

Our monitoring of this trajectory places data-center operators and engineering teams in the Gulf and Egypt on the brink of an operational imperative. In the region’s hot, arid climate, liquid cooling is the backbone of expansion in supercomputing complexes, yet reliance on it brings doubled costs for producing desalinated water and heightened consumption sensitivity. If you manage the infrastructure of a computing facility or are building a sovereign AI system, fluid waste or reliance on slow laboratory testing raises operating costs and threatens service continuity under climate conditions that cannot tolerate pump failures. Shifting from monitoring chip temperature alone to instant measurement of cooling-fluid alkalinity and cleanliness redefines the skill set required for facility management, as hydraulic safety now forms an integral part of ensuring the stability of the AI models themselves.

This deal reveals that the maturity of the AI industry is no longer measured solely by the number of model parameters, but by the resilience of the physical infrastructure that supports it on the ground. Investment in pipe chemistry and flow sensors demonstrates that every minute of downtime costs millions of dollars, and that computing sustainability starts with the details of the fluids flowing between chips before it reaches algorithmic outputs.