More compute.
Less energy.
Compute deserves intelligent cooling. arflo combines thermal physics with AI for precise control, from the chip to the data center.
Less cooling energy.
Cool only as much as you need.
More thermal control.
Understand load peaks. Respond earlier.
Full transparency.
Understand every control decision.
Intelligence follows heat.
It starts with compute.
Every workload changes the power demand of your infrastructure. And the heat your cooling system needs to remove.
Same workload.
Two control strategies.
What happens when cooling follows compute? Explore three load profiles in a simplified thermal model and compare temperature and cooling electricity demand.
- IT load
- 95 %
- Static
- 61.3 °C
- Adaptive
- 60.1 °C
Simplified single-node model, not measured data or a savings forecast. Same initial temperature (60 °C), same inlet (22 °C), identical load. Model parameters are illustrative; actual results depend on the system.
What makes a fair comparison ↗One model.
The whole system.
The engineering idea behind arflo: connect operational data with thermal understanding and derive appropriate cooling control inputs.
Your infrastructure
Temperatures · Compute load · Cooling state
arflo
Physical model + adaptive optimization
Your cooling
Setpoints · Control inputs · Feedback
Understand the data.
Which signals are available? We establish measurement points, data quality and your system interfaces.
Evaluate the model.
Predictions and measurements are compared. Load changes and model limitations belong in the evaluation.
Plan control together.
Control inputs, approvals and fallback behavior are defined with the operations team for the specific system.
Integration scope, model deployment and access to controls are agreed for each pilot project.
Discuss integration ↗Where compute matters.
And every watt.
From individual racks to complex infrastructure. One intelligent view of your thermal system.
Data Centers
THERMAL EFFICIENCYUse cooling energy precisely. Understand thermal reserves and keep operations in view.
02AI & High Performance
HIGH-DENSITY COMPUTEDynamic GPU workloads create new demands. Your cooling should keep up.
03Edge & Enterprise
DISTRIBUTED SYSTEMSBeyond large data centers: thermal visibility for distributed infrastructure.
ENGINEERED IN STUTTGART, GERMANY ↗The thinking
behind the technology.
Thermal fundamentals, meaningful comparisons and the path into a control loop. A closer look at the questions behind arflo.
Why room temperature does not describe the chip.
Between a workload and room temperature lie materials, thermal interfaces and time. That path matters when you want precise control.
Read article · 3 MIN↗What makes a fair cooling comparison.
Lower electricity consumption becomes meaningful when workload, system boundaries and thermal conditions support the comparison.
Read article · 4 MIN↗From model to control loop.
Between a plausible prediction and a change to cooling lie practical integration decisions. They are part of the engineering.
Read article · 3 MIN↗Get more
from your
infrastructure.
Show us your challenge. We’ll show you how arflo can make your cooling smarter.