Oil & Gas
Stop waiting for rigs to break.
Rank rotating kit and line sections by real failure risk, then fix them in planned windows — not when production is already offline.
The Problem
Reactive maintenance is expensive — and predictable.
When a seal or bearing goes, the bill is rarely the part. It is lost barrels, marine spreads, and a crew that has stopped planning and started reacting.
Your historian and SCADA already hold the precursors. Most stacks only alarm after the trip; almost none tell you which asset is next in line.
Calendar inspections look busy. They rarely line up with where degradation is actually accumulating.
How it works
From scattered tags to a ranked work list.
Connect existing data
SCADA, historians, MQTT, ERP — standard interfaces, no rip-and-replace. We read what you already log.
Twin the assets that matter
Pipelines, compressors, turbines: physics-based state on top of live tags so “normal” tracks how you are actually running.
Forecast and rank risk
Degradation trends, criticality, and history feed one priority list — who gets the next window, not who is due on a spreadsheet.
Close the loop
Alerts land with context your maintenance lead can defend: suggested window, likely mode of failure, trace back to the signals.
Results
What teams measure once it's in production.
- 25–40%
- reduction in maintenance costs and unplanned downtime
- Extended
- asset lifespan through condition-based scheduling
- Weeks
- advance warning on failures, not hours after
Who this fits
Who this fits
Maintenance leads, reliability engineers, and asset managers on upstream, midstream, and offshore sites who need fewer surprise trips and a work list the CFO will not dismantle in Q3.
Straight talk
Common questions before a PO.
- "Our sensor infrastructure is old."
- That's most of our clients. We integrate with legacy SCADA, OPC, MQTT, and whatever protocols you're running. If your equipment generates data, we can work with it.
- "We tried predictive maintenance software before."
- And it probably died after the pilot. Our MLOps pipelines keep models retrained and accurate in production — not just in a demo environment.
- "How fast can we see results?"
- Most clients see measurable impact within the first 8–12 weeks. Not a roadmap — actual numbers in your maintenance reports.
Next step
See which assets are next in line — before the alarm.
Thirty minutes on your tags and historians: where a twin would sit, and what the first useful outputs look like.