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AVEVA and NVIDIA Partner to Build Next-Gen Digital Twin Architecture for AI Factories

AVEVA has developed a new lifecycle digital twin architecture that delivers industrial intelligence for gigawatt-scale AI factories accelerated by NVIDIA.

March 18, 2026. By News Bureau

AVEVA has announced a strategic collaboration with NVIDIA to develop an advanced lifecycle digital twin architecture designed to power gigawatt-scale AI factories. This initiative aims to significantly enhance GPU efficiency, streamline deployment, and accelerate the scalability of next-generation AI-driven data centres.

AVEVA’s engineering and operations software is now integrated into the NVIDIA Omniverse DSX Blueprint, enabling the creation of both physical and digital modules for large-scale AI factories. This approach mirrors established engineering, procurement, and construction (EPC) methodologies, ensuring faster and more reliable deployment of complex infrastructure.

The collaboration leverages AVEVA’s robust portfolio, including its CONNECT industrial intelligence platform and digital twin capabilities, to accelerate time-to-token for AI workloads, enable high-fidelity simulations and visualisation, support collaborative design at scale, maximise GPU utilisation.

AVEVA’s partnership extends to industry leaders such as Schneider Electric and ETAP. Together, they are advancing the design, simulation, construction, and optimisation of AI factories using the Omniverse DSX framework.

Customers can import OpenUSD SimReady assets into AVEVA Unified Engineering via a new converter. This enables reuse of existing digital assets, creation of new designs, access to high-fidelity simulation environments powered by NVIDIA Omniverse. With AVEVA Asset Information Management a single source of truth is maintained, equipment and system updates are synchronised, alignment is ensured from design through operations.

With AVEVA Process Simulation, customers can model and run simulations of advanced liquid-cooling networks for AI factories to refine designs and maximise cooling efficiency. AVEVA’s PI System enables customers to aggregate IT and OT data across NVIDIA Omniverse DSX Exchange. In time this will be extended to include the NVIDIA NV-Tesseract model for anomaly detection and forecasting, enabling customers to interpret telemetry in real time from BMS, EPMS, cooling systems, server racks and workloads, all at giga-scale. This will transform efficiency throughout the lifecycle.

Customers can use AVEVA Operations Control and Unified Operations Center to manage data centre infrastructure which comprises of electrical (UPS, switchgear, PDU, generator etc.), mechanical (chiller, CDU etc.) and safety systems into one scalable unified platform using a templatised situational awareness approach. This will enable operators to accelerate root cause analysis, recommend actions, monitor alerts and identify degradation trends as they push densities higher. This will enable customers to leverage AVEVA’s trusted expertise when delivering new high density AI factories.

Rob McGreevy, Chief Product Officer, AVEVA said, “AI Factories are fast becoming the industrial-scale engines of the global digital economy. To drive this transformation, AVEVA and NVIDIA are creating a new approach to digital twin deployments, founded on domain-specific expertise, pioneering software and operational excellence.“

“Together, our companies are creating this new digital twin at scale, combining SimReady assets, NVIDIA hardware, and IT and OT data-driven insights to design, build and AI-optimise the intelligent industries of the future,” he added.

“The rapid rise of gigawatt-scale AI Factories requires a new class of industrial intelligence to optimise the entire lifecycle of these massive data centres, from initial design to real-time operations,” said Vladimir Troy, vice president, AI Infrastructure, at NVIDIA.

“By integrating AVEVA’s engineering and simulation software into the NVIDIA Omniverse DSX blueprint, we are providing developers with a unified digital twin architecture to accelerate the deployment and efficiency of the world’s most advanced AI infrastructure,” he added.
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