Stop Reacting.
Start Predicting.
SupInsight uses Bayesian multi-variable causal inference to calculate RTO breach probability with a 95% confidence interval — hours before any incident occurs. Triggers automated remediation within 300ms.
Core Capabilities
Real-Time Health Portrait
Multi-dimensional monitoring data streams in real-time, forming a holistic health score for every business system. Correlates infrastructure state, network latency, storage IO, and business availability.
RTO Breach Prediction
Instead of alerting after disaster strikes, SupInsight calculates "the probability of RTO breach in the next 60 minutes" and triggers automatic optimization before any SLA violation.
RLHF Self-Evolution
Continuous training on PB-scale historical drill data. Incorporates operator feedback via Reinforcement Learning from Human Feedback. Dynamic model updates based on real workload patterns.
Bayesian Inference Architecture
P(RTO > T | E) = [P(E|R) · P(R)] / P(E)
- IOPS / Latency
- Packet Loss / Jitter
- CPU / Memory / Queue
- Bayesian Network PGM
- P(RTO>T|E) = [P(E|R)·P(R)] / P(E)
- Historical Priors + RLHF
- Trigger Pre-emptive Snapshot
- Reroute Replication Path
- Throttle Non-Critical IO
See SupInsight Predict Your Next Incident
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