AI for refinery & plant operations
Your plant never sleeps. Now neither does its watch.
QOTAN.ai monitors every unit around the clock, cuts the alarm flood down to the few issues that matter, and tells your team what will fail, and when, before it becomes an emergency.
- P1P-204B charge pump · bearing wearVibration up 38% over 9 days. Failure likely in ~17 days. Swap to P-204A in the next window.
- P2Heater H-101 · 212 alarms → 1 root causeFuel gas pressure controller oscillating. Consequential alarms suppressed.
- OPTAtmospheric column · setpoint adviceRaise top reflux 2% to recover diesel from the naphtha cut. Awaiting approval.
What QOTAN.ai does
One co-pilot for the whole plant, from the control room to the maintenance shop.
Process Optimization
Continuously adjusts setpoints for distillation columns, catalytic crackers and hydrotreaters to maximize high-value product yields and lower energy use.
Learn more →Predictive Maintenance
Analyzes vibration, pressure and temperature data from pumps, compressors and turbines to flag failing equipment weeks before it breaks down.
Learn more →Anomaly Detection
Filters out alarm noise on control-room dashboards and highlights the real operational risks before small issues cascade into shutdowns.
Learn more →Safety & Compliance
Pulls real-time data together for environmental monitoring, logs health and safety incidents, and keeps an automatic audit trail.
Learn more →Operator assist
Your operators shouldn't have to be the alarm filter.
EEMUA 191 guidance puts a manageable load at about one alarm every ten minutes per operator. During an upset, consoles can show hundreds. Fatigue sets in and real warnings get lost in the noise.
- Watches every unit, every shift. Nothing depends on someone happening to look at the right trend at the right time.
- Triages alarms as they fire. Groups consequential alarms under their root cause and ranks what's left by risk.
- Explains, then recommends. Each item shows the evidence and a suggested response, so operators act while the problem is still small.
Illustrative 24-hour shift on a single crude unit.
Predictive maintenance
Knows what needs maintenance, and when.
QOTAN.ai learns how each pump, compressor and turbine behaves when it's healthy, spots the early signatures of wear, and forecasts when each asset is likely to fail.
- A dated forecast for every critical asset, with a confidence range rather than a vague warning.
- Fits your maintenance windows. Recommends the latest safe date so crews and parts are planned, not rushed.
- Connects to your CMMS. Raises work orders with the failure mode and the sensor evidence attached.
How it works
Built on the data your plant already collects.
No new sensors to start. QOTAN.ai reads from your existing systems and runs where your security team needs it to: on-premise, in a private cloud or air-gapped.
Connect
Read-only links to your historian, DCS alarm journal and CMMS over standard interfaces such as OPC UA. Nothing is written to your control system unless you enable it.
Learn
Models are trained on your own operating history, unit by unit and asset by asset, so they understand how your plant normally runs.
Advise
Ranked, explained recommendations reach the console, the maintenance planner and the compliance log. Your people stay in control of every decision.
See QOTAN.ai on one of your units.
Start with a scoped pilot on a single unit or equipment class, measured against your own baseline.