Schneider Electric, NVIDIA and HPE launch industrial AI agents

Bringing AI to the factory floor

Schneider Electric, NVIDIA, and HPE have partnered to launch Industrial AI Agents for process and heavy industries. This collaboration aims to move AI applications into industrial operating environments where reliability and safety are paramount. The goal is to help companies manage plants that require strict adherence to cybersecurity and energy standards.

The new offering combines HPE Private Cloud AI with Schneider Electric's operational technology software and automation expertise. It is specifically designed for industries running continuous processes, such as chemicals or pulp and paper. These sectors need to monitor and adjust operations without causing any disruptions to their output.

The collaboration reflects a broader trend among technology suppliers to move AI beyond robotics and autonomous vehicles. Instead, the focus is on monitoring and adjusting the systems that power critical global industries. By embedding intelligence directly into these operations, the companies hope to improve resilience and sustainability.

How edge AI agents function

The system is built to operate at the edge, which means the AI runs close to the source of the data rather than in a remote cloud. This approach addresses common industrial concerns regarding data sovereignty and the high costs of scaling AI. By keeping data within site boundaries, operators can maintain tighter control over sensitive information.

HPE Private Cloud AI provides the underlying infrastructure layer for these operations. Schneider Electric's EcoStruxure Industrial Insights applications allow customers to manage and govern multiple AI agents from a single environment. This setup is intended to simplify security oversight and lifecycle management for plant operators.

The technical foundation includes NVIDIA Nemotron open AI models. These models work with the private cloud and monitoring platform to turn vast amounts of operational data into actionable insights. This allows the system to monitor, reason, and optimize industrial operations in real time.

Three types of industrial agents

The initial product set includes three specific types of agents tailored for different industrial needs. OT Monitoring Agents combine equipment settings, process topology, and maintenance history to identify emerging issues. These agents can recommend corrective actions and verify the results to keep production running smoothly.

Cybersecurity Agents are designed to correlate network activity with control system behavior and asset settings. They aim to detect abnormal conditions and assess how they might affect operations. If a threat is detected, the agents can recommend a response and confirm that the system has returned to a stable state.

Energy Optimisation Agents focus on energy consumption patterns and equipment performance. They identify opportunities to adjust operations to improve efficiency. These agents assess the impact of those adjustments on both energy use and overall plant performance to ensure the best balance for the facility.

Real-world application and impact

Schneider Electric highlighted CMPC Chile as an early example of the operational foundation for this system. For the past three years, CMPC has used a monitoring system to track the health of control systems in its pulp and paper operations. This deployment provides a single view of servers, workstations, and switches across the facility.

The existing monitoring setup helps CMPC identify issues earlier and diagnose faults more quickly to avoid costly disruptions. The companies are now positioning this proven foundation as the base for introducing the new AI agents. This transition will allow specialists to investigate problems faster while keeping humans in control of critical decisions.

The partnership aims to turn large volumes of data into specific actions that can be used inside plants. By combining industrial expertise with AI and edge computing, the companies want to help customers transform raw data into better outcomes. This move lays the groundwork for more autonomous operations in heavy sectors worldwide.

Security and data sovereignty

A major barrier to industrial AI adoption has been the concern over protecting sensitive data and critical systems. HPE emphasized that private cloud infrastructure at the edge allows operators to expand AI use while retaining control. This ensures that data handling remains private and secure within the organization's own boundaries.

The partnership is designed to address the specific needs of industrial organizations that want to use AI but fear cloud risks. By bringing AI closer to where data is generated, the solution maintains the security and privacy required by these businesses. It provides a way to scale technology without sacrificing the protections necessary for heavy infrastructure.

Ultimately, the goal is to provide a turnkey AI factory solution for process industries. This allows for the development of what the companies call Physical AI. This type of intelligence is embedded in the systems that power the world's critical industries, making them more efficient and resilient.