Last Updated 1 day ago by Kenya Engineer
As data centres evolve to support AI-intensive workloads, traditional maintenance models—built around fixed schedules or post-failure responses—are increasingly misaligned with operational reality. Addressing this shift, Vertiv has launched Vertiv™ Next Predict, an AI-powered, managed predictive maintenance service designed for modern data centres and emerging AI factories.
The new service applies machine learning and field intelligence to continuously assess the real-time condition of critical infrastructure assets. Rather than relying on time-based servicing assumptions, Vertiv Next Predict analyses equipment behaviour to identify risk patterns before faults occur, enabling operators to intervene early and avoid unplanned downtime.
From Reactive Maintenance to Predictive Intelligence
With rising rack densities and compute intensity driven by AI workloads, operators face tighter thermal margins, higher power variability, and greater system interdependence. Vertiv Next Predict is engineered to provide end-to-end predictive visibility across power, cooling, and IT infrastructure, supporting a more resilient operating model at scale.
The service uses AI-based anomaly detection to flag deviations from expected performance, followed by predictive algorithms that estimate potential operational impact. This allows risks to be ranked and prioritised, ensuring attention is focused where it matters most. Built-in root cause analysis isolates contributing factors, while prescriptive recommendations guide corrective action.
Execution is carried out by Vertiv-trained services teams, closing the loop from insight to intervention and reducing mean time to resolution.
Built for AI-Scale Infrastructure
A key design principle behind Vertiv Next Predict is scalability. The service currently supports a growing portfolio of Vertiv power and cooling platforms, including battery energy storage systems (BESS) and liquid cooling technologies, which are becoming critical enablers for high-density AI deployments.
Importantly, the architecture is designed to extend alongside future technologies, aligning with Vertiv’s grid-to-chip approach—linking utility power, energy storage, thermal management, and IT loads into a unified operational framework.
According to Ryan Jarvis, Vice President for Global Services at Vertiv, the shift is both strategic and necessary:
“As compute intensity rises and infrastructures evolve, data centre operators need to stay ahead of potential risks. Vertiv Next Predict enables a move away from calendar-based maintenance to a proactive, data-driven strategy—using continuous condition monitoring to mitigate risk before operations are impacted.”
Operational Implications
For operators, predictive maintenance translates into higher uptime, better asset utilisation, and improved lifecycle planning—all critical as AI workloads place unprecedented demands on infrastructure. By embedding analytics directly into operations, Vertiv Next Predict positions maintenance as a continuous optimisation function, rather than a periodic intervention.
Backed by decades of field experience, a global services footprint, and AI-enabled analytics, Vertiv’s latest offering signals a broader industry transition: from maintaining infrastructure after failure, to engineering resilience before failure occurs.
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