Schneider Electric teams with NVIDIA & HPE on industrial AI

Schneider Electric has formed a strategic collaboration with NVIDIA and HPE to develop industrial AI systems for process industries, with the first product a set of Industrial AI Agents at the edge.

The group is targeting sectors such as pulp and paper and other heavy industries, where operators run continuous processes and must balance reliability, safety, cybersecurity and energy use. The offering combines HPE Private Cloud AI, Schneider Electric's operational technology software and NVIDIA's AI models.

The companies describe the work as a route to what they call Physical AI in industrial settings, moving AI processing closer to factories and plants instead of relying on remote cloud systems. The approach is intended to keep operational data within site boundaries while allowing software agents to monitor systems, assess issues and support responses in real time.

Three barriers

Executives said the collaboration is intended to address three common barriers to wider industrial AI deployment: data sovereignty, cybersecurity and the cost of AI use. At many industrial sites, operational data is considered too sensitive or too tightly regulated to move off site, while increased connectivity can expose equipment and networks to additional risk.

They also argued that running AI workloads in the cloud can become expensive as usage expands across multiple plants, assets and operations. By placing inference and data processing at the edge, industrial groups can reduce data transfer and related usage costs while retaining more control over deployment, they said.

Customers will be able to deploy and manage the AI agents through Schneider Electric's EcoStruxure Industrial Insights applications, which are intended to provide a single environment for governance, lifecycle management and security oversight.

The first three agents focus on operational technology monitoring, cybersecurity and energy optimisation. According to the companies, the monitoring agent draws on operational data, equipment configurations, alarms, maintenance records and engineering context to identify emerging issues and assess likely operational effects.

The cybersecurity agent is designed to correlate network activity, control system behaviour, asset configurations and operational events to detect abnormal conditions and support response measures. The energy optimisation agent combines process and consumption data with operating conditions and production requirements to identify adjustments aimed at improving efficiency.

Industrial test case

A practical example is already in use at CMPC Chile, part of Empresas CMPC, one of Latin America's largest pulp, paper and packaging producers. Schneider Electric said CMPC Chile has spent the past three years using its Operational Technology Monitoring System in production across continuous pulp and paper operations.

The system gives CMPC teams a single view of control systems, servers, workstations and switches, helping staff spot issues earlier and set maintenance priorities. That installed base now provides a foundation for future use of the new AI agents, Schneider Electric said.

"The next generation of industrial innovation will be driven by intelligence embedded directly into industrial operations," said Gwenaelle Huet, Executive Vice President, Industrial Automation, Schneider Electric.

"While much of today's focus is on autonomous machines, we see a significant opportunity to apply Physical AI to the industrial systems that power the world's critical industries. Together with NVIDIA and HPE, we are bringing together expertise in automation, AI and edge computing to help customers transform operational data into action, improving resilience, efficiency, cybersecurity and sustainability while laying the foundation for more autonomous industrial operations," Huet said.

Sri Kodali, Global Head of Developer Relations - Energy and Utilities at NVIDIA, linked the project to the challenge of using large volumes of industrial data more effectively.

"Industrial operations generate vast amounts of data, but turning that data into action remains one of industry's biggest challenges. By combining NVIDIA Nemotron open AI models and HPE Private Cloud AI, a turnkey AI factory solution, with Schneider Electric's industrial expertise and OTMS platform, Industrial AI Agents can monitor, reason and optimize operations in real time, accelerating the path to Physical AI for process industries," Kodali said.

HPE said the project reflects customer demand for AI systems that do not require sensitive operational data to leave protected environments. Its role centres on the private cloud platform used to run the systems close to industrial assets.

"Industrial organizations see real opportunities to use AI, and they want to be sure their sensitive data and critical systems will remain protected. Through our collaboration with NVIDIA and Schneider Electric, we're helping customers use HPE Private Cloud AI to bring AI closer to where their data is generated and decisions are made. This gives customers a way to expand AI use across their facilities while maintaining the security, privacy and control their businesses require," said Alexia Clements, SVP, Hybrid Cloud Solution Sales at HPE.

CMPC also pointed to the operational case for adding AI tools on top of existing monitoring systems.

"For the past three years, OTMS has helped us improve visibility into the health and availability of our control systems. In continuous industrial operations, identifying issues early is critical to protecting production and avoiding costly disruption. Looking ahead, we see significant potential for AI Agents to build on this proven foundation, helping our specialists investigate issues faster and move more effectively from insight to action, while keeping people in control of critical decisions," said Matías Jory, Digital & Process Manager, Industrial Operations Vice-Presidency, CMP.