Accenture has launched Physical AI Orchestrator, a new cloud-based solution that enables manufacturers to transform traditional plants and warehouses into software-defined facilities.
Announced at NVIDIA GTC in Washington, D.C., the platform integrates NVIDIA Omniverse technologies with AI agents from Accenture’s AI Refinery, allowing real-time simulation, optimisation and control of physical manufacturing environments.
In these software-defined facilities, virtual replicas mirror real-world operations, helping detect issues, simulate changes, and guide automated systems. By using accurate physics and AI reasoning, the system can instantly adjust to shifts in demand, quality, or scheduling, turning physical infrastructure into a self-learning, adaptive system.
Accenture said the solution has already been deployed in sectors such as high tech, life sciences, and consumer goods. Among the early adopters is Belden, a network and data solutions provider that used the Orchestrator to develop a virtual safety fence for factories and warehouses. The system can automatically stop or reroute robots when humans enter restricted zones, improving worker safety without halting production.
In the life sciences sector, one company used the tool to simulate biologics and vaccine production conditions, reducing batch variability and improving shelf life. Similarly, a consumer goods manufacturer used digital twins to optimise warehouse layouts, achieving a 20% boost in throughput and cutting capital costs by 15%.
“Physical AI Orchestrator acts as a brain for a physical space,” said Prasad Satyavolu, Americas Lead for Accenture’s Digital Engineering and Manufacturing Service, Industry X. “Powered by NVIDIA Omniverse and Accenture AI Refinery, it is designed to make agentic AI and physical AI part of the fabric of manufacturing.”
The system’s key features include AI-powered reality capture for generating photorealistic 3D twins, vision analytics for tracking movements and workflows, and XR extensions for immersive collaboration and training.
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