ROCKWELL AUTOMATION TO ADVANCE INDUSTRIAL INTELLIGENCE THROUGH EDGE-BASED GENERATIVE AI WITH NVIDIA NEMOTRON

EQS-News: Rockwell Automation, Inc. / Key word(s): Product Launch ROCKWELL AUTOMATION TO ADVANCE INDUSTRIAL INTELLIGENCE THROUGH EDGE-BASED GENERATIVE AI WITH NVIDIA NEMOTRON 13.11.2025 / 21:50 CET/CEST The issuer is solely responsible for the content of this announcement. Purpose-built AI model delivers instant insights and control for industrial teams, on the edge, offline and everywhere work happens

MILWAUKEE, Nov. 13, 2025 /PRNewswire/ -- Rockwell Automation, Inc. (NYSE: ROK), one of the world's largest companies dedicated to industrial automation and digital transformation, today announced a breakthrough in bringing generative AI directly to the industrial edge. Rockwell is introducing its integration of NVIDIA Nemotron Nano, a purpose-built small language model (SLM) optimized for FactoryTalk Design Studio and other Rockwell product workflows, marking a major step in real-time intelligence for industrial teams.

In collaboration with NVIDIA, Rockwell is leveraging the open-source Nemotron-Nano-9B-v2 model and NVIDIA NeMo to deliver an edge-based generative AI capability designed specifically for industrial environments. Nemotron Nano distillation techniques provide the foundation for an SLM that can run in edge environments with less space and power than a traditional data center. By fine-tuning the model with data used by FactoryTalk Design Studio Copilot, Rockwell is creating a solution that demonstrates new potential for industrial automation professionals.

Built for use across design, development, production and maintenance workflows, the model operates seamlessly on HMI panels, appliances, desktop IDEs and server or private cloud environments. It supports both edge and air-gapped deployments, offering improved reasoning, predictability and responsiveness compared to other SLMs.

Early evaluations show the step change value of this model having new reasoning, parallel processing and key performance breakthroughs that enable it to stand out in the SLM space. Results highlight the model's strong fit for industrial edge scenarios where instant responsiveness, data security and offline operation are essential.