A Los Angeles startup says it is adapting aerospace thermal-management techniques to cool data centers using significantly less electricity and water. The approach targets a growing bottleneck as AI workloads drive data center expansion worldwide.
As artificial intelligence pushes data centers to consume record amounts of power and water, a Los Angeles startup is betting that the solution will come from an unexpected place: rocket science.
The company says it has adapted cooling technologies originally designed for aerospace and defense applications to manage heat in modern data centers more efficiently. The pitch is simple but ambitious — reduce the massive energy and water footprint of facilities that now sit at the core of the global digital economy.
The timing is critical. Utilities, municipalities, and cloud providers are increasingly struggling to balance AI-driven infrastructure growth with sustainability and resource constraints.
Aerospace engineering meets digital infrastructure
The startup, based in Southern California’s aerospace corridor, applies advanced thermal-control principles commonly used in rockets and spacecraft — environments where heat management is a matter of survival.
Instead of relying on traditional evaporative cooling or energy-intensive chillers, the company’s system emphasizes precise heat transfer, optimized airflow, and materials engineered to dissipate extreme temperatures efficiently.
While the company has not publicly disclosed all technical details, it says early deployments suggest meaningful reductions in both electricity consumption and water usage compared with conventional data center cooling systems.
That claim has attracted attention as hyperscale operators confront mounting criticism over the environmental cost of AI.
Why cooling has become a crisis point
Data centers already account for a growing share of global electricity demand, and AI workloads are accelerating that trend. Training and running large language models requires dense computing clusters that generate enormous heat.
Traditional cooling systems often rely on water-intensive evaporation or power-hungry refrigeration. In drought-prone regions, water use has become especially controversial, drawing scrutiny from regulators and local communities.
For cloud providers and enterprises alike, cooling efficiency is no longer just a cost issue — it is a permitting, reputational, and political one.
A growing market under pressure
The startup’s approach enters a competitive but rapidly expanding market. Established data center operators and equipment vendors are investing heavily in liquid cooling, immersion systems, and alternative architectures to keep pace with AI demand.
What differentiates the aerospace-derived approach, the company argues, is its ability to operate efficiently across a wide range of temperatures without heavy reliance on external water or mechanical cooling.
For investors, the appeal lies in scalability. If the technology performs as promised, it could be retrofitted into existing facilities rather than requiring entirely new builds.
Implications for AI infrastructure growth
The push for better cooling solutions reflects a broader reality: AI infrastructure is running into physical limits. Power grids, water supplies, and local zoning laws are becoming as important as chips and software.
Startups offering incremental efficiency gains may struggle to stand out. Those that materially reduce resource consumption, however, could become essential partners for cloud providers racing to expand capacity without triggering backlash.
For cities like Los Angeles — where climate concerns, energy costs, and infrastructure constraints intersect — locally developed solutions carry additional symbolic weight.
What comes next
The company says it is continuing pilot projects with data center operators and plans to scale manufacturing if results hold. Independent verification and long-term performance data will be critical to winning broader adoption in a conservative industry.
Still, the premise underscores a shift underway across tech infrastructure: as AI growth collides with environmental reality, innovation is increasingly coming from outside traditional software circles.
In this case, the future of digital computing may depend on lessons learned far above the Earth’s atmosphere.
