Energy intelligence for AI Factories starts at rack level

Why energy is now the limiting factor!

AI workloads behave differently from traditional IT workloads. GPU clusters generate sudden power peaks, high sustained loads and rapidly changing demand patterns. Liquid cooling systems add further complexity to the energy equation.

Traditional data centre management tools were not designed for this reality. Without detailed, real-time insight into energy consumption, operators face:

• Increased risk of overloads
• Inefficient capacity utilisation
• Limited ability to scale AI infrastructure
• Higher operational and energy costs

In AI Factories, energy is not a background utility. It is a critical production resource.

The missing link: rack-level energy intelligence

Many AI and grid management platforms focus on high-level optimisation: workload orchestration, grid pricing or sustainability reporting. However, these platforms depend entirely on the quality and granularity of the underlying energy data.

True energy intelligence starts in the rack.

Without accurate measurement at input, branch and outlet level, it is impossible to:

• Attribute energy consumption to specific servers or GPU nodes
• Correlate compute workloads with power usage
• Detect risks before they impact availability
• Automate optimisation safely

The role of intelligent PDUs

Intelligent PDUs form the physical foundation of energy-aware AI data centres. Schleifenbauer PDUs are designed to support high-density HPC and AI environments by providing:

• Real-time energy measurement at rack level
• Outlet-level monitoring for precise workload attribution
• Reliable data for integration with DCEM, DCIM and orchestration platforms
• Remote switching with outlet switching delay and near zero voltage switching
• Safe handling of inrush current and high-power equipment

This level of detail enables AI Factory operators to move from reactive monitoring to proactive control.

From energy data to energy intelligence with EnerTree

Hardware alone is not enough. Energy data must be accessible, interpretable and actionable.

EnerTree DCEM software complements Schleifenbauer PDUs by providing:

• Centralised real-time energy visibility
• Historical data and trend analysis
• Alarm management and risk detection
• Support for capacity planning and compliance reporting

EnerTree is delivered without licence fees and operates within the customer’s own infrastructure, ensuring full control over energy data and long-term flexibility.

Built for scalable AI infrastructure

AI Factories require infrastructure that can evolve. Schleifenbauer does not rely on fixed standard PDU models. Each PDU is engineered to fit the existing rack and power architecture, without additional cost or extended lead times.

This approach ensures:

• Maximum flexibility for future AI expansion
• No compromise on safety or performance
• Infrastructure decisions remain in the hands of the data centre operator

Conclusion

AI Factories depend on more than powerful compute platforms and advanced software. They require energy intelligence at the physical layer.

By combining intelligent PDUs with EnerTree DCEM software, Schleifenbauer provides the foundation for scalable, stable and sustainable AI data centres. Because in an AI Factory, energy intelligence does not start in the cloud or the grid. It starts in the rack.