AI factories are some of the most complex operations in the world, combining GPUs, CPUs, switches, DPUs, and SuperNICs alongside schedulers, orchestration services, security controls, and a rapidly changing software stack. Deploying this infrastructure effectively is a challenge. But so is being able to validate that the infrastructure, software, and policies work together for the workloads the business intends to run. To minimize time to first token, AI factory operators can’t wait until hardware arrives before validating it.

Connect AI agents to the digital twin

A node-based digital twin simulation is a high-fidelity, executable representation of an AI factory’s infrastructure and operational interfaces. Unlike a physical replica, it gives platform teams a safe, API-accessible environment in which to model the hardware topology and software stack, exercise change, observe behavior, and validate outcomes before a production change is made.…