AI Diagnostics
Root-Cause Intelligence Engine

Instantly identify failures, predict breakdowns, and reveal hidden issues across your entire facility. Your ops team gains the intelligence of a 20-year expert — in seconds.

How It Works

1. Data Ingest

AI pulls patterns from sensors, work orders, HVAC data, electrical panels, and historical trends.

2. AI Pattern Analysis

ML models compare symptoms, anomalies, and failure signatures across your entire building network.

3. Root-Cause Diagnosis

AI identifies the most likely failure source — and explains why — in plain language your techs understand.

Real Diagnostic Examples

Air Handler Failure

Diagnosis: Overheating due to clogged filter + damper misalignment
Confidence: 94%
Recommendation: Replace filter, recalibrate damper, schedule vibration check.

Electrical Panel Warning

Diagnosis: Breaker #7 overloaded from HVAC-4 startup surge
Confidence: 89%
Recommendation: Shift load to Panel LP-3 or upgrade circuit.

Boiler Pump Prediction

Prediction: Pump failure expected in 14 days
Cause: Bearing degradation + thermal imbalance
Recommendation: Order replacement + schedule outage window.

What the AI Engine Can Do

Analyze HVAC, electrical, plumbing, and life-safety data
Predict failures with ML forecasting
Compare anomalies across hundreds of buildings
Detect dangerous load patterns in real time
Identify asset inefficiencies and wasted energy
Suggest repairs and procedures step-by-step
Learn every building’s “normal” behavior over time
Auto-write work orders into your CMMS

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See how FacilitiesViewer transforms troubleshooting into instant intelligence.

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AI DiagnosticsRoot-Cause Intelligence Engine