POWERED BY BRAINS

Predict the Failure. Plan the Fix.

Avoid Unexpected Downtime.

Your maintenance schedule shouldn't be based on time intervals when it can be based on actual equipment condition. Brains monitors your rotating assets continuously — compressors, pumps, motors — and predicts failures 15+ hours before they happen, with the engineering context that explains why.

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Maintenance When Its Needed,

Not When Its Scheduled.

Calendar-based maintenance replaces equipment on schedule — whether it needs it or not. Condition-based maintenance replaces equipment when the data says it needs replacing. Brains provides the data, the diagnosis, and the engineering context to make that decision with confidence.

Screenshot of Anomaly Detection in Brains by Drishya AI

Evidence Based Maintenance With Signals.

Continuous Rotating Asset Monitoring

Compressors, pumps, motors, turbines — monitored continuously through operating patterns, not just vibration thresholds. Brains learns each asset's normal behavior and detects degradation patterns as they develop, not after they cause a failure.

Failure Prediction With Engg. Context

A bearing degradation pattern means different things on different equipment. Brains knows the difference because it runs on the Contextual Graph — connecting the vibration signature to the equipment type, its design specifications, its operating conditions, and its maintenance history.

Model-Driven Time-to-Failure Estimation

Not just "this asset is degrading" — but "at the current rate, this asset will fail in approximately 72 hours." Your maintenance team schedules the intervention. The equipment runs until it actually needs attention. No premature replacements.

Multi-Signal Correlation

Equipment failure rarely announces itself through a single sensor. Brains correlates vibration, temperature, pressure, flow, and power consumption simultaneously — identifying the multi-signal patterns that precede failures before any single threshold is breached.

Maintenance Planning Integration

Brains delivers failure predictions with enough lead time for your maintenance team to plan — order parts, schedule crews, coordinate with operations. 15+ hours of advance warning turns emergency response into planned maintenance.

ESP & Artificial Lift Optimization

Electrical submersible pumps, gas lift systems, and rod pump operations — each with unique failure modes and set-point requirements. Brains monitors artificial lift equipment and optimizes set-points based on actual well performance, not static initial configurations.

Every unnecessary scheduled shutdown costs production. Every unexpected failure costs more. The sweet spot is maintaining exactly when the equipment needs it — not before, not after. That's what condition-based maintenance delivers.

Frequently Asked Questions

Common questions about condition based maintenance.

Ready to Maintain by Condition Instead of Calendar?

Connect your asset data. See failure predictions with engineering context — 15+ hours before the failure arrives.

Condition Based Maintenance | Drishya AI