Predictive Decision Engine
Low-latency anomaly detection and predictive operational analytics system for streaming enterprise data feeds.
A research prototype that analyzes real-time streaming transactional telemetry to forecast operational bottlenecks before they occur.
The Research Challenge
Traditional batch analytics produce static historical reports, failing to alert operations teams to real-time anomalous patterns.
Engineering Approach
We train lightweight temporal transformer models on time-series telemetry streams to trigger automated alerts upon state drift.
Real-Time Stream Vectorization
Temporal Transformer Anomaly Detection
Sliding Window Metric Aggregation
Automated Alert Webhook Dispatcher
Benchmarking streaming latency under 100,000 telemetry events per second.
Integrating automated root-cause analysis sub-agents.
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