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Anomaly Detection Dashboard
Feed in time-series data — network traffic, transactions, sensor readings, server logs — and AI flags anomalies in real time with severity scores and natural language explanations.
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Overview
Four statistical detection algorithms plus LLM-powered explanations identify anomalies in streaming or batch time-series data. The system doesn't just flag anomalies — it explains what they likely mean in plain English.
What You'll Learn
- Statistical anomaly detection methods (Z-Score, IQR, Isolation Forest, Rolling Stats)
- Real-time streaming anomaly detection with SSE
- LLM-powered root cause analysis and explanation
- Severity classification and alert systems
Key Capabilities
- 4 detection algorithms with different strengths
- Live streaming mode with real-time anomaly flagging
- 4 simulated data types (network, transactions, sensors, servers)
- AI-generated explanations for each detected anomaly
- Batch analysis with CSV upload support