Prevent Failures. Do Not Just React to Them.
Predictive Maintenance analyzes inspection data, service history, and operational patterns to forecast equipment failures - so you can schedule repairs on your terms, not on the asset's terms.
Reactive Maintenance Is the Most Expensive Kind
Unplanned equipment failures cost 3-10x more than planned maintenance - in emergency repairs, lost production, and customer penalties.
Calendar-based maintenance over-services healthy equipment and misses degradation patterns on others.
Critical failure data is trapped in inspection forms nobody reviews until something breaks.
When an asset fails in the field, the ripple effect delays every downstream job.
How Predictive Maintenance Works
Data Aggregation
Inspection results, work order history, run-hours, and sensor data are aggregated into a unified asset health profile.
Failure Prediction
Machine learning models identify degradation patterns and predict failure windows - weeks before the breakdown occurs.
Prescriptive Scheduling
Recommended maintenance actions are scheduled automatically based on predicted failure timing and crew availability.
Built for Operators
Predictions Built on Your Operational Data
Most predictive maintenance tools require expensive sensor deployments. OpsFlo builds predictions from the inspection and work order data your crews already capture - delivering value from day one.
Stop Guessing.
Start Building.
OpsFlo is the single source of truth for industrial operators. Stop losing revenue to disconnected field data.