Two-phase cooling for AI and HPC

Thermal Intelligence for High-Density Data Centers

We’re making two-phase cooling deployable in the data centers you already have. STAR, our Stabilized Two-Phase Architecture, is how we do it.

See how we build

The problem

Compute is outgrowing the cooling around it

Rack power is climbing from tens to hundreds of kilowatts. Two-phase cooling, which absorbs heat by boiling, can carry that load; the hard part is deploying it reliably at rack scale.

Cooling power

Chillers, pumps and water set the ceiling on rack density long before the chip does.

Deployable capacity

Installed power stays stranded when racks can’t be cooled reliably under real AI workloads.

Deployment speed

Custom cooling loops and facility rework add months to every new site.

Our technology

Meet STAR

Our Stabilized Two-Phase Architecture keeps two-phase cooling stable under fast-changing GPU loads, and fits the racks and CDUs data centers already run.

250 kW+per rack
≤1.05PUE
Drop-infor existing racks and CDUs

Design targets.

Rendered STAR rack from the PhaseQ film

How we build

Analysis, testing and expertise, working as one

The PhaseQ team links system-scale analysis, component-scale analysis and experiments, so each informs the others and every design decision draws on all three. Agentic AI speeds up the routine work; our engineers make the calls.

How PhaseQ designs STARA loop: system-scale analysis with STAR-ROM and component-scale analysis with CAD, meshing and CFD inform each other; both feed design decisions, which set the priorities for experimental validation; test data flows back to refine the models. The PhaseQ team leads from the center of the loop, and agentic AI accelerates the modeling work. The loop produces STAR, deployable two-phase cooling for 250 kW+ AI racks.Accelerated by agentic AIoperating conditionscomponent behaviorinforms decisionssets test prioritiestest datarefines the modelsPhaseQ teamleads every decisionSystem-scale analysisIn-house STAR-ROM modelComponent-scale analysisCAD, meshing and CFDDesign decisionsInformed by both scalesExperimental validationRun in order of priorityvalidateddesignSTARDeployable two-phase coolingfor 250 kW+ AI racksHow PhaseQ designs STARAccelerated by agentic AISystem-scale analysisIn-house STAR-ROM modelComponent-scale analysisCAD, meshing and CFDoperatingconditionscomponentbehaviorPhaseQ teamleads every decisionDesign decisionsInformed by both scalessets test prioritiesExperimental validationRun in order of prioritytest data refines the modelsSTARDeployable two-phase coolingfor 250 kW+ AI racks

Path to deployment

  1. Now

    Modeling and design

    System- and component-scale analysis, in-house

  2. Next

    Lab-scale validation

    Test data to confirm and refine the models

  3. Then

    Rack-scale proof of concept

    STAR running on existing infrastructure

  4. Later

    Deployment

    With data center partners

Partner with us

Let’s deploy it together

We’re looking for partners to help validate and deploy STAR.

  • Data center operatorsPlanning high-density AI capacity
  • GPU cloud and HPC teamsRunning racks at the edge of what cooling allows
  • Hardware and CDU partnersBuilding the systems STAR plugs into