Sightline EDM®: Automated Anomaly Detection in Real-Time
Machine learning anomaly detection, AI, and big data analytics make it possible to identify anomalies in data or potential data outliers in large data sets that wouldn’t be detectable by a human user alone.
By establishing and using historical baseline data across ecosystems and combining it with data collected in real-time, your company can identify issues before they create high-cost production interruptions. Sightline EDM® automates anomaly-based monitoring, saving your company time and money.
Machine Learning Anomaly Detection Prevents Potential Issues As They Occur
Collect real-time data across thousands of inputs throughout your ecosystems with Sightline EDM®. We have identified the ideal evaluation metrics for anomaly detection while establishing a historical baseline, allowing you to identify data outliers that would otherwise be difficult to find.
We don’t just make it easier to detect anomalies, we make it easier to track the data. Sightline EDM® simplifies time series anomaly detection by providing a holistic view of your data in one central dashboard whether you work in one facility or several locations.
Sightline EDM® uses AI and time series anomaly detection to trace historical activity and identify potential data outliers. Establishing your historical baseline allows the software to measure the significance of the flagged anomalies.
Configurable Off-the-Shelf Analytics Solution
Unified Dashboard with Optional Drill-Down
Usable, Right Out of the Box
Scalable Usability for Teams of All Sizes
Standard Integrations Across Systems
Stop High-Cost Interruptions with Time Series Anomaly Detection
- Advanced data analytics, anomaly detection, and root cause analysis
- Holistic view of information with data intelligence dashboard
- Real-time data collection and custom alerts
- End-to-end data security