NVIDIA has announced a major expansion of its Omniverse Blueprint for AI factory digital twins, which is now available in preview. The updated blueprint incorporates new ecosystem integrations across power, cooling, and networking, welcoming industry leaders such as Delta Electronics, Jacobs, and Siemens to its roster. These join existing partners like Cadence, Schneider Electric with ETAP, and Vertiv, creating a unified platform for designing and simulating the intricate components required for building digital twins of Artificial Intelligence factories.
The expanded Omniverse Blueprint leverages NVIDIA’s GB200 NVL72-powered reference architectures and OpenUSD asset libraries, allowing developers to combine detailed 3D and simulation data into a single, unified virtual model. This virtual environment enables engineering teams to design, simulate, and optimize every aspect of Artificial Intelligence factory infrastructure— from power systems to cooling solutions and networking—well before physical construction begins. Key integrations with platforms such as Cadence Reality Digital Twin and ETAP enhance simulation capabilities, enabling thorough testing of thermal flows and power distribution for high-intensity Artificial Intelligence workloads.
Collaboration among new and existing partners is further enhanced by the adoption of SimReady standards, which ensure that assets are physics-based, interoperable, and ready for high-fidelity simulation. Siemens is actively building 3D models to these specifications, Delta Electronics is contributing equipment models, and Jacobs is involved in overall workflow optimization. The SimReady standardization workflow, now publicly available, sets out standardized methods for developing digital twin assets, streamlining the creation and testing of digital twins for critical data center infrastructure, with a particular focus on electrical and thermal management.
NVIDIA’s expanded blueprint marks a pivotal shift in how Artificial Intelligence factory infrastructure is developed and operated. By enabling more collaborative and standardized digital twin development, it helps engineering teams minimize risk, optimize operational performance, and accelerate time to deployment for next-generation Artificial Intelligence facilities. With this ecosystem approach, NVIDIA is reshaping the digital infrastructure landscape to support the scaling demands of Artificial Intelligence factories worldwide.
