Schneider Electric and NVIDIA unveil new AI data center designs, digital twins, and agentic AI tools to scale efficient, high-performance infrastructure.
Schneider Electric has unveiled a new wave of AI data centre innovations in collaboration with NVIDIA and AVEVA, marking a significant step forward in the design and operation of next-generation “AI factories.”
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Announced at NVIDIA GTC, the developments focus on improving how AI infrastructure is designed, simulated, deployed, and managed at scale. The collaboration reflects a broader industry push to support the rapid growth of compute-intensive AI workloads with more efficient and resilient infrastructure.
At the core of the announcement is a new reference design built for NVIDIA Vera Rubin NVL72, NVIDIA’s latest rack-scale system. The design introduces advanced power and cooling capabilities, including 480 VAC power distribution and higher operating temperatures to improve energy efficiency. It also features a redesigned IT room architecture that clusters AI racks with shared networking and storage to optimise performance and reduce latency.
The system supports multiple GPU operating modes, such as MaxP and MaxQ, enabling operators to balance performance and efficiency while increasing token generation output per watt, a key metric for large-scale AI deployments.
In parallel, Schneider Electric and AVEVA introduced a new lifecycle digital twin architecture integrated into the NVIDIA Omniverse ecosystem. This solution allows operators to simulate real-world data centre environments before physical deployment, using advanced modelling of power distribution, thermal dynamics, airflow, and control systems.
By enabling multi-domain simulation, the platform helps reduce engineering risks, improve accuracy, and accelerate time-to-market for AI infrastructure projects.
The partnership is also exploring the use of agentic AI in data centre operations. Early testing with NVIDIA Nemotron models focuses on automating alarm management, allowing AI systems to analyse real-time IoT data, identify root causes of issues, and recommend corrective actions. The goal is to improve operational efficiency while supporting human technicians with faster, more precise insights.
These latest developments build on a long-standing collaboration between Schneider Electric and NVIDIA, spanning power systems, cooling technologies, and intelligent software integration. Together, the companies are positioning themselves at the forefront of AI infrastructure, combining hardware, software, and simulation tools to enable scalable, efficient, and sustainable AI data centres.
As demand for AI compute continues to surge, such integrated approaches are becoming critical to supporting the next phase of global AI deployment.
Why Schneider Electric and NVIDIA Partnership Matters to MENA
This development goes beyond global tech headlines—it directly ties into how the MENA region is positioning itself in the AI race. Countries like the UAE and Saudi Arabia are investing heavily in hyperscale data centers and sovereign AI infrastructure, and partnerships like this set the technical blueprint for what those deployments will look like.
The introduction of energy-efficient power systems, advanced cooling, and digital twin simulations is particularly relevant in MENA, where climate conditions and energy optimisation are critical factors in data center design. These innovations between Schneider Electric and NVIDIA could significantly reduce operational costs while enabling the region to scale AI workloads sustainably.
There’s also a strategic angle. As governments push for localised compute capacity, reducing reliance on overseas infrastructure, technologies that improve performance per watt and enable predictive operations will become essential. This is especially true for sectors like smart cities, energy, fintech, and autonomous systems—areas where MENA is actively building competitive advantage.
In simple terms, this isn’t just about better data centers. It’s about giving the region the infrastructure backbone needed to support its long-term AI ambitions.
