To support rapid AI growth

Increasing densities, equipment varieties, and services have led to complexity challenges. What the market needs is integrated solutions from a provider that can support the AI wave at every step

The question may not be whether cooling infrastructure can operate on 800VDC. It’s whether the supplier ecosystem can evolve quickly enough to support that future

The choices organizations make today will influence not only performance and reliability, but also how the next generation of data centers is designed and operated.

As data center power density climbs, successful infrastructure planning depends on understanding how power availability, cooling strategy, and deployment timelines influence one another

A power-first mindset amid AI at scale and aging infrastructure

In addition to protecting critical infrastructure, AI-ready UPSs also help optimize AI investments, enhance operational resilience, and mitigate the impact of large-scale AI workloads on the electric grid

What happens after the hardware is commissioned?

The companies that succeed in the AI era will be the ones that solve the infrastructure challenge at every layer between the grid and the rack

Why solar energy and battery storage are critical pieces of the data center power puzzle

Getting the basics right

… it's facing a convergence

AI demand has made 18–24 month build timelines unsustainable, is modular the answer?

AI’s transient power demands are rendering legacy UPS architectures obsolete. Nickel-zinc chemistry offers a high-rate, fail-safe alternative, enabling high-density compute without systemic retrofit risks

Why the industry must continue to look beyond the grid

Insights for owners to navigate power quality, cooling, and backup energy in the age of inference

Industry and government must partner to scale the commercially available tools that improve utilization of our existing grid now, advancing both speed to power and affordable electricity for all consumers

As hyperscale growth continues and sustainability expectations intensify, sustainable electrification will increasingly depend on how intentionally the industry approaches electrical infrastructure decisions

The benefits of RDHxs for today's AI environments

By prioritizing integration from the outset, organizations can reduce risk, improve predictability, and build systems that perform reliably at scale

Battery energy storage is becoming essential for AI data centers, helping bridge grid constraints, support resilience, and accelerate speed-to-power

The differences between power-dense training and low-latency distributed inference show why the AI era calls for workload-led UPS battery selection

Fiber no longer functions as a passive backbone interconnecting largely uniform compute systems. Optical infrastructure now operates as an active architectural layer carrying multiple workload classes with distinct operational characteristics

Greater demands for AI workloads require greater amounts of data center power