AI Infrastructure.
Power systems for the intelligence revolution.
Power electronics purpose-built for AI training clusters, inference servers, and edge AI hardware. Ultra-high-density power conversion, GPU rack power systems, liquid cooling drives, and digital twin monitoring for the next generation of compute infrastructure.
AI workloads demand
power electronics designed for them.
AI training workloads generate power transients unlike any industrial application — instantaneous load swings of 50–80% as GPU clusters start and stop compute jobs. Standard UPS and drive systems are not designed for this. Power Flux AI builds power conversion and cooling drive systems optimized for AI compute profiles: fast transient response, ultra-high power density, and intelligent load management that anticipates demand from workload schedulers.
"Every major hyperscaler is now designing custom power electronics for AI infrastructure. Power Flux AI brings that capability to Tier-2 and Tier-3 data centers, cloud providers, and AI hardware manufacturers who cannot afford a Google-scale power team."
Purpose-built for
this industry.
AI Cluster Power Distribution
High-density power conversion for GPU and TPU compute clusters. Handles instantaneous load transients from AI workload scheduling. 48V bus architecture with fast dynamic response <1 ms.
Liquid Cooling Drive Systems
Variable speed drives for direct liquid cooling pumps and immersion cooling systems. Precision flow control for GPU cold plate cooling. Integrates with workload schedulers for predictive cooling.
Edge Inference Power Systems
Compact, ruggedized power systems for edge AI hardware — autonomous vehicles, smart cameras, industrial robots. Wide input range, high efficiency at light load, fanless thermal design.
NVMe & Storage Array Power
Power conversion for all-flash NVMe storage arrays and persistent memory systems. High efficiency, low EMI, hold-up time compliance for sudden power loss protection.
AI-Native Digital Twin
Digital twin that integrates directly with AI cluster management software. Real-time power consumption per GPU rack, cooling efficiency, and predictive maintenance alerts. REST API for DCIM integration.
PUE Optimization Platform
Power Usage Effectiveness monitoring and optimization. AI-driven cooling control that correlates compute workload with cooling demand — reducing PUE from 1.4–1.6 toward 1.1.
What we deliver.
Power the intelligence revolution.
Start with an Architecture Sprint — your AI infrastructure power and cooling requirements, proposed architecture, and a 90-day prototype roadmap.