Detect What’s Truly Abnormal — Not Just What’s Loud
Filter out the noise of dynamic networks to focus only on the anomalies that impact your revenue.
Why Traditional Alerts Fail
Threshold Overload
Fixed thresholds generate a flood of false positive alerts in dynamic, changing networks.
85%
false positives
Silent Failures
Critical, subtle performance shifts are missed because they don't cross a static line.
42%
issues missed
Alert Fatigue
NOC teams suffer from alert fatigue, eventually ignoring the very alerts meant to protect them.
73%
alerts ignored
Wasted Resources
Traditional anomaly detection often flags busy periods as broken, leading to wasted engineering hours.
4.2hrs
wasted daily
The Cascade Effect
How alert failures compound
Result: Burnt-out teams and missed critical incidents
How Anomaly Detection Works
Data Collection
PRI, PSS, CI, MRR metrics
Baseline Learning
Dynamic behavior envelope
Pattern Analysis
Sliding time windows
Anomaly Scoring
Impact-weighted detection
Only Meaningful Alerts
80% fewer alerts, 100% more relevant
Normal Behavior Envelope
This model uses machine learning to learn the Normal Behaviour Envelope of your specific network paths.
Multi-Metric Context
It monitors a combination of metrics—including PRI, PSS, CI, and MRR—across sliding time windows.
Dynamic Baselines
Rather than using fixed numbers, it calculates a dynamic baseline that understands your network's unique cycles.
Impact-Weighted Scoring
Any deviation is scored based on its statistical significance and business impact, ensuring you only get alerted for meaningful changes.
Watch Anomaly Detection in Action
See how PathMetrics filters noise and surfaces only the anomalies that truly matter.
Anomaly Detection Demo
2:52 min • Context-aware alerting
The Path Intelligence Edge
It is Context-Aware.
It prioritizes the Business Pain, not just the raw metric spike.
Time-Aware Intelligence
It understands that a latency spike at 3:00 AM on a Sunday might be ”normal” for your backup window, while the same spike at 10:00 AM on a Monday is a critical anomaly.
Anomaly Scorecard
Dynamic scoring against the learned normal range
Anomaly Detection
Real-time scoring
72
/ 100
Anomaly Score
Statistically Significant Deviation Detected
Business Benefits
Impact Metrics
Dramatic Reduction in Alert Fatigue
80% fewer alertsReceive 80% fewer, but 100% more relevant, alerts.
Detection of Silent Failures
Subtle detectionCatch the subtle degradations that don't trigger traditional threshold alerts.
Increased Trust in Data
100% actionableWhen an alert fires, your team knows it's a real issue that requires action.
Reliable Automation Triggers
Safe automationSafely trigger automated rerouting because the signal-to-noise ratio is high.
Optimized On-Call Cycles
Happy engineersKeep your engineers focused on innovation, not chasing false positives.
Ideal Use Cases
Stop chasing noise. Start catching anomalies.
Get intelligent alerting that understands your network’s unique patterns and only surfaces what truly matters.
See Anomalies That MatterNo credit card required • See results in minutes
80%
Fewer Alerts
100%
Relevant