Description
Owl Analytics is a behavioral analytics platform that uses unsupervised machine learning to automatically identify normal behavior patterns in data and detect significant deviations without requiring predefined rules or thresholds. The platform's unique approach to anomaly detection works across time-series, transactional, and multi-dimensional data, scaling to billions of data points while maintaining computational efficiency. By focusing on behavioral pattern recognition rather than conventional statistical methods, Owl Analytics enables organizations to discover previously unknown anomalies, emerging trends, and subtle changes in complex data environments that traditional analytics systems would miss.
Key Features
- Unsupervised behavioral learning
- Multi-dimensional pattern recognition
- Automated anomaly detection
- Zero-configuration setup
- Explainable detection results
Use Cases
- Cybersecurity threat detection
- Financial fraud identification
- Operational anomaly discovery
- Network behavior analysis
- Supply chain risk detection
Pricing Model
Enterprise licensing with processing-based tiers
Integrations
Security information systems, Log management platforms, Data lakes, Streaming data sources, Alerting systems
Target Audience
Security operations teams, Fraud analysts, Data scientists, Risk management professionals, IT operations specialists
Launch Date
2016
Available On
Enterprise software, Cloud deployment, Edge integration
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