Operations
Intelligence stays intelligent.
Performance, drift, and safety monitored in real time.
Live Dashboard
Real-time system health
Four critical metrics tracked continuously across every deployed system.
Model Accuracy
97.3%↑ +0.4%
Latency P95
142ms↑ -12ms
0ms< 200ms400ms
Drift Score
0.12
Error Rate
0.8%
ALL SYSTEMS NOMINAL
Last updated: just nowObservability
Four layers of monitoring
From infrastructure to business outcomes — every signal has a watcher.
Application Metrics
Layer 01What's tracked
Request volumeResponse timesThroughputQueue depth
Alert thresholds
P95 latency > 200ms
Error rate > 1%
Queue depth > 1000
Model Performance
Layer 02What's tracked
Accuracy / F1Hallucination rateDrift scoreToken usage
Alert thresholds
Accuracy < 95%
Drift > 0.3
Hallucination > 2%
Infrastructure Health
Layer 03What's tracked
CPU / GPU utilisationMemory pressureDisk I/ONetwork saturation
Alert thresholds
CPU > 85%
Memory > 90%
Disk > 80%
Business Outcomes
Layer 04What's tracked
Task completion rateUser satisfactionCost per inferenceROI tracking
Alert thresholds
Completion < 90%
CSAT < 4.0
Cost > budget
Human Oversight
Escalation timeline
From anomaly detection to human-driven resolution — every step has a response-time target.
Step 01
Alert
Anomaly detected by monitoring system
Target: < 30s
Step 02
Triage
Automated severity classification and routing
Target: < 2 min
Step 03
Review
Human operator examines context and impact
Target: < 15 min
Step 04
Action
Remediation applied — rollback, retrain, or escalate
Target: < 1 hr
Feedback Loop
Continuous improvement cycle
A closed loop that turns monitoring signals into model improvements.
Monitor
Detect
Analyze
Improve
Deploy
Ask the AI how we monitor your system.
Real-time observability, drift detection, and human escalation — configured for your stack.