AI scores every job, crew, site, and piece of equipment for risk - ranked by consequence, not just probability. Proactive, not reactive.
Risk in most operations is managed by gut feel and past experience. A foreman knows which jobs tend to go sideways. A supervisor knows which crew pushes too hard. A maintenance manager knows which equipment is overdue for attention. But gut feel doesn't scale, doesn't document, and doesn't give you a ranked list of what to address this week.
TMI's Risk Scoring system quantifies what experienced people already sense - and extends it across the entire operation. Every job, crew, site, and asset scored continuously against historical incident data, sensor streams, weather, crew certification records, and cost burn patterns. Not a dashboard full of raw readings. A ranked list of what's at risk, ordered by consequence and probability, with the context needed to act.
When a combination of factors - an overdue inspection, a crew on their third consecutive long shift, and a weather event - converges on a single site, the system surfaces it before anyone's phone rings about a problem. Risk managed before it becomes an incident. Not reconstructed from it.
Production rates, pressure readings, crew certifications and hours, equipment maintenance history, cost burn, weather data, and safety event logs - all ingested and analyzed continuously. Not a single data point in isolation. The system looks for the combinations of signals that precede incidents in your historical data and surfaces them before they compound.
Every identified risk scored on two dimensions: probability of occurrence and consequence if it happens. A high-probability, low-consequence event ranks below a low-probability, catastrophic one. The system surfaces what actually deserves attention today - not what's merely statistically common. The ranked list is actionable, not overwhelming.
When a risk threshold is crossed, the alert goes to the person with authority to act on it - not a generic notification to a general inbox. The alert includes the contributing factors, the recommended intervention, and the consequence window if no action is taken. Decision-ready information, not raw data requiring interpretation.
Real-time operational monitoring paired with pattern-recognition across the full asset fleet - the combination that surfaces risk before it becomes a consequence.
A real-time monitoring system across your full operational data stream. Production rates, pressure readings, crew movement, cost burn, and safety events watched simultaneously. Anomalies ranked by severity and routed to the right person before they compound into incidents.
A continuously running model that watches sensor streams, work order history, and usage patterns to surface equipment failure risk before failure happens. Not threshold alerts. Pattern recognition across the entire asset fleet, ranked by consequence, not just probability.
Risk models built and trained on your specific operational history, incident database, and regulatory environment. Generic risk scores replaced with models that reflect how your operation actually fails.
Well integrity failures, pressure events, and pipeline anomalies have safety, regulatory, and production consequences that are severe and immediate. Risk scoring across the full well and asset portfolio - ranked by consequence - gives operations teams the prioritized list they need before anything on it becomes an emergency call.
Every active site is a combination of equipment, crew, weather, and schedule pressure that produces a unique risk profile. The system scores each site daily - flagging the ones where the combination of factors looks like the ones that preceded past incidents. Intervention before the event, not investigation after it.
Unplanned downtime in manufacturing and utilities carries cascading consequences. Pattern recognition across the full equipment fleet surfaces the assets most likely to fail in the next 30 days - ranked by production impact, not just maintenance urgency. Maintenance prioritized where it matters most.
Risk doesn't announce itself. But it leaves patterns in your data before it turns into an incident. We'll show you what those patterns look like in your operation.
TMI