AVEVA has announced a major collaboration with NVIDIA to develop a new lifecycle digital twin architecture designed to accelerate the design, deployment, and operation of gigawatt‑scale AI Factories. The partnership integrates AVEVA’s engineering and operations software directly into the NVIDIA Omniverse DSX Blueprint, creating a unified industrial intelligence layer for modern hyperscale data centers.
The collaboration aims to maximise GPU efficiency and streamline the engineering of AI Factories through domain‑specific simulation, collaborative design environments, and reusable digital modules applying methods long used in large industrial EPC projects.
“AI Factories are becoming the industrial engines of the digital economy and digital twins are the key to building them with speed, accuracy, and intelligence.”
— Rob McGreevy, Chief Product Officer, AVEVA
Working alongside strategic partners Schneider Electric and ETAP, AVEVA is extending its proven industrial methodologies to the rapidly emerging AI Factory category. Through this integration, customers can bring OpenUSD SimReady assets into AVEVA Unified Engineering, maintain a single source of truth through AVEVA Asset Information Management, and simulate advanced liquid‑cooling networks using AVEVA Process Simulation.
AVEVA’s PI System will further unify IT and OT data across the NVIDIA Omniverse DSX Exchange, with future support for NVIDIA’s NV‑Tesseract model to drive real‑time anomaly detection and forecasting across massive data‑center environments.
Operationally, AVEVA Operations Control will provide a unified monitoring and control layer spanning electrical, mechanical, cooling and safety systems enabling faster diagnostics, higher density management, and improved lifecycle performance.
Rob McGreevy said the collaboration brings together “SimReady assets, NVIDIA hardware, and IT‑OT intelligence to design, build and AI‑optimise the intelligent industries of the future.”
The integrated digital twin architecture is available to customers beginning this year.
