A physics-grounded AI agent platform that continuously sanitizes, maps, and analyzes Distributed Control System data to advise panel operators on energy-optimal targets and warn of process deviations hours before alarms trigger.
Modern processing plants generate millions of telemetry records daily. Most of this data is only accessed to perform failure analysis after the fact. We utilize this readily available stream of information to detect faults early, advise operator action, and optimize plant conditions.
The AI Agent is shipped with physics-first, plant-agnostic design basis configurations, enabling immediate integration on Low-Pressure Storage and Heat Exchange assets.
Demineralized water vessel with blanket nitrogen gas padding, overpressure safety systems, and multiple duty/standby transfer pumps.
Process fin-fan cooling bay cooling a hot single-phase stream by drawing ambient air via multiple axial fans.
To validate performance without model overfitting, the AI Agent prototype was tested blind against 30 days of synthetic DCS logs generated by an independent physics simulator.
Correctly categorized fault families and rotating-equipment bearing wear modes across all blind runs.
Detected and classified anomalies in a median of 0.58 hours (~35 minutes) from initial fault event onset.
Simulator generated 30 days of 60s logs with injected sensor dropouts, random noise, and non-standard tagging.
The AI Agent analyzed the logs without knowing the locations, durations, or types of faults injected.
An independent Scorer compared the Agent’s reports against the hidden Ground Truth to calculate accuracy and speed.
Observe raw telemetry logs stream from the plant simulator on the left, and watch the AI process core output standard, validated operator advisories on the right.
The AI agent has detected a fan belt slip event on cooling fan bay HX_201. Fan rotational speed has dropped, motor stator current has unloaded, and the bundle cooling approach has risen.
Industrial facilities operate under strict data safety bounds. We bypass the traditional cloud compliance bottlenecks entirely.
The agent is installed on client-approved local servers or hypervisors within the facility's control network. Zero process data leaves your firewall.
Operational logic updates are packaged and updated locally. The agent operates in complete isolation, minimizing cyber-attack vectors.
No external APIs, no public cloud endpoints, and no outbound tunnels. Total ownership of your plant data remains in-house.
"With process safety at the forefront, we designed Supreme Cortex to work from the control room, not from a remote cloud server. By combining on-the-ground operational experience with edge-computed physics, we empower panel operators and support engineers with real-time, actionable diagnostics to keep systems running within optimal operational boundaries."
Led global plant commissioning, dynamic start-up, field operations, and control room (DCS) troubleshooting across downstream refineries, LNG plants, and midstream processes.
Specialized in plant start-ups, control loop troubleshooting, equipment debottlenecking, and process performance optimization based on chemical engineering principles.
Discuss deploying the AI Agent in "Shadow Mode" on your historians, or request detailed physics simulator reports.
info@supreme-cortex.ca
Calgary, Alberta, Canada