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Vertiv Targets Proactive Uptime With Next Predict Managed Service

Vertiv (NYSE: VRT) introduced Vertiv Next Predict, an AI-powered managed service designed to shift data center maintenance from reactive and time-based models to predictive operations. The service analyzes asset behavior across power, cooling, and IT systems to identify risks before failures occur, targeting modern data centers and AI-scale facilities where uptime and performance margins continue to narrow.

Vertiv positions Next Predict as part of its broader AI infrastructure portfolio, applying machine-learning models to continuously monitor operating conditions and flag anomalies early. The platform evaluates potential operational impact, prioritizes response, and supports root-cause analysis to guide prescriptive actions. Corrective measures then move into execution through Vertiv’s global services organization.

The service supports a growing range of Vertiv power and cooling platforms, including battery energy storage systems (BESS) and liquid-cooling components, and is architected to scale with future technologies. Vertiv frames the approach as a grid-to-chip service model intended to integrate new infrastructure elements over time as AI workloads push higher density and complexity.

“Data center operators need innovative technologies to stay ahead of potential risks, as compute intensity rises and infrastructures evolve,” said Ryan Jarvis, vice president of Vertiv’s global services business unit. “Vertiv Next Predict helps data centers unlock uptime by shifting maintenance from calendar-based routines to a proactive, data-driven strategy.”

🌐 Analysis

Predictive maintenance has become a focal point as AI factories concentrate unprecedented power density and thermal loads into fewer sites, raising the cost of unplanned outages. Vertiv’s move aligns with a broader industry push to embed analytics and automation into power and cooling stacks, as peers expand digital services to complement hardware portfolios and address AI-driven operational risk.

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