Build Agentic Optimizations that Cut Supply Chain Planning from Weeks to Minutes

Building an advanced superchip like the NVIDIA Blackwell means coordinating over a million parts. Demand shifts weekly, but supply chain decisions (e.g., sourcing) must be locked in months ahead. At that scale, traditional planning can fall short — weeks of manual work, compounding complexity, and exponential risk with every decision. NVIDIA applied an AI-first planner to its own internal supply chain. Built on agentic workflows and powered by the NVIDIA cuOpt, an open-source GPU-accelerated optimization engine, planning cycles were cut from weeks to minutes. The cuOpt Supply Chain Agent takes natural language problem descriptions, converts them into mathematical optimization models, and solves them using GPU-accelerated cuOpt. It leverages cuOpt agent skills that are also available out of the box for specialized supply chain workflows. From sourcing and workforce allocation to fulfillment and what-if scenarios, it orchestrates end-to-end decisions fast, with clear and explainable results. This agent is completely open-source and ready to deploy for your own supply chain workflows.