Industrial Outlier Detection & Analysis App.
Industrial Outlier Detection & Analysis App
Explainable outlier detection for industrial operations
Outlier Detection & Analysis App is powered by innovative technology from Maya HTT.
Identify and explain data abnormalities
Detecting anomalies is easy. Understanding them is not.
The Industrial Outlier Detection and Analysis App identifies anomalies in high-dimensional manufacturing and operations data and explains why it happened, not just that it happened.
The result: Get fewer false alarms, faster diagnosis, and a continuously improving understanding of your industrial systems.
Built for high-dimensional industrial data
Detect subtle and complex deviations across hundreds or thousands of correlated signals.
Key capabilities
- Optimized for manufacturing machine data and operations time series
- Handles multivariate, non-linear, and highly correlated features
- Robust to noise, drift, and real-world industrial variability
From outlier detection to root-cause insight
Get an explanation for every outlier.
Key capabilities
- Identifies the most contributing variables driving each outlier
- Highlights how and where behavior deviates from normal operation
- Provides actionable insight engineers can investigate immediately
Group, label, and learn from similar outliers
Stop analyzing anomalies one by one.
Key capabilities
- Automatically clusters similar outliers across time
- Enables fast labeling and categorization by engineering teams
- Builds a shared, structured understanding of abnormal behaviors
From interpretable outliers to explainable anomalies
Transform past incidents into future intelligence.
Key capabilities
- Reuses learned explanations for recurring anomaly patterns
- Evolves from raw detection to named, explainable anomaly classes
- Creates a growing knowledge base of operational behaviors over time
