Your infrastructure isn’t just competing against today’s AI workloads — it’s racing a hardware cycle that turns over every 24 months. Atlas One is engineered for legacy, current, and next-generation accelerators from day one, so the next chip release doesn’t mean a rebuild.
Atlas One runs fully waterless. No cooling towers, no evaporative loss: while still hitting a targeted PUE of 1.0–1.1, avoiding the water-vs-efficiency tradeoff most cooling systems force.
A GPU thermal ceiling is the point at which a cooling system can no longer remove heat fast enough to prevent an accelerator from throttling. Atlas One is your solution.
Most AI infrastructure gets measured by rack count—but the metric that actually matters is tokens produced per square foot. Here’s how Atlas One’s immersion cooling and waterless design push more power toward compute instead of fighting heat.
One AI infrastructure question used to be: how many servers can we deploy? Atlas One asks a better one — how many tokens can it actually produce, how fast can it come online, and how easily can it scale? A modular, factory-tested platform built to answer all three at once.
Everybody calls these CRACs. Half the time they’re not. And if you’re planning an AI retrofit, getting that distinction wrong can send you down the wrong mechanical path. CRAH vs CRAC is one of the most common mix-ups we run into, and it’s an understandable one. Both units sit in the data center doing the same basic job, both look similar from the front, and both show up in the same conversations about room-level cooling. But they’re mechanically different machines, and which one you have (or which one you’re specifying for a new build) changes how your facility scales, how it fails, and what it costs to run.
RDHx vs CRAH is the question we get from almost every facilities team that’s hit a density wall. Your CRAH units have kept the room comfortable for a decade. Then rack densities start climbing — 30, 50, 80 kW and beyond — and the room-level approach gets increasingly difficult to manage: hot spots emerge, airflow requirements climb, and fans work harder to move enough conditioned air to the load. This isn’t a “which is better” question in the abstract. It’s a “which fits this rack” question, and the honest answer is usually both, doing different jobs in the same white space.
Passive RDHx: use the airflow you already have. Active RDHx: actively manage the airflow you need. Passive vs active RDHx is a decision that gets skipped more often than it should. Once a facilities team has settled on rear door heat exchangers as the right architecture for a high-density rack, the next question—passive or active—gets treated like a footnote. It isn’t.
Immersion cooling sounds simple: put the servers in dielectric fluid and remove the heat. The real decision starts with what that fluid does next.
Single-phase immersion cooling and two-phase immersion cooling both submerge your hardware directly in a dielectric fluid instead of cooling it with air—but that’s roughly where the similarity ends. The fluid behaves completely differently in each system, and that difference drives almost every other decision: what tank you need, how much fluid you’re buying, what maintenance looks like, and how much density you can actually support per rack.
Colocation rack density has shifted dramatically — from 5kW per rack in the virtualization era to 50kW and beyond for AI and HPC workloads. Legacy air-cooled halls weren’t built for this. Here’s what that means for operators sitting on aging infrastructure, and how Infrastructure Density Uplift changes the math.
Whether you need to upgrade your existing setup or design something new from scratch, we have the know-how and technology to help you get more computing power while spending less on cooling.