No-code Industrial AI for oil and gas operations.
Compressor trips cost real production hours, flaring is now a board-level metric, and operators are already drowning in DCS alarms.
- 14:22HIGHCMP_042 residual +3.2σ
- 11:08MEDDRY_B drift trend
- 07:41LOWBLR_01 efficiency dip
- 02:15HIGHPUMP_07 cavitation pattern
The operating pressures we built around.
Rotating equipment uptime
Compressors and turbines are the spine of production.
Flaring and emissions reporting
Flare hours and CO2 e are reported externally and watched internally.
Alarm flood
Threshold alarms fire late, and too often — the control room tunes out.
The work that pays for itself first.
The platform capabilities that matter most here.
- Anomaly detection →
Critical compressors, turbines, and valves.
- Forecasting →
Upset conditions and flare risk.
- Data Explorer →
Cross-unit comparison for energy and fuel benchmarking.
Adjacent proof — midstream operator
"We replaced two threshold alarms with one anomaly model — same coverage, far less noise."
What we read, how often, and how it gets here.
Historian (PI / AVEVA), DCS, SCADA, compressor OEM packages
vibration, motor current, suction/discharge T&P, fuel gas, flare totalizer
1–5s for rotating equipment; 1min for production
Read-only Gateway; opt-in write-back only behind site safety governance.
Reporting and audit, built into the workflow.
Emissions & flaring reporting
Traceable kg CO2 e and flare hours, per asset and per event.
Safety-critical alarm governance
Audit log of every model-driven alert and operator response.
Management of Change (MOC)
Setpoint and threshold proposals routed through your MOC workflow.
One-pager for oil & gas teams.
A printable summary covering the use cases, expected KPIs, data needed, and integration notes on this page — written for plant leadership and IT/OT.
See it on your own oil & gas data.
A 30-minute working session with an industry specialist. Bring one unit and your top KPI — we'll come back with a working model proposal.