AI Agentic Network Control Tower

Cisco · Meraki · Ericsson | Multi-Agent AIOps Platform

Network Health
87%
Active Incidents
3
Predicted Failures
2
Automation Rate
64%
SLA Risk
High

AI Agent Team (Mesh)

Anomaly Agent Active
Correlation Agent Active
Root Cause Agent Active
Prediction Agent Active
Recommendation Agent Active
Remediation Agent Approval
Learning Agent Learning

Incident Reasoning & Workflow

Device: Switch-23 (Delhi Branch)

🔍 Anomaly: Packet drops & latency spike

🔗 Correlation: QoS policy update + traffic surge

🧠 Root Cause: Duplex mismatch (92% confidence)

📈 Prediction: SLA breach in 36 hours

💡 Recommendation: Auto-correct port configuration

Detect
Correlate
Analyze
Predict
Recommend
Act

Automation Console

Network Topology

Switch-23
Router-11
AP-07

Prediction & Forecast

Learning & Optimization

✔ Incident patterns learned

✔ RCA confidence improved

✔ Automation rules refined

🔐 Network Security + AI

AI Monitoring Active

Threats Detected

7

Risk Score

78%

Zero Trust

Enabled

Auto Remediation

Partial

🚨 Active AI-Detected Threats

DDoS Traffic Spike Detected via AI traffic anomaly
Lateral Movement Suspected East-West traffic deviation
Firewall Policy Drift Mismatch with baseline

🤖 AI Security Insights

  • High probability of bot-driven traffic from ASN-24560
  • VPN gateway shows abnormal authentication attempts
  • Firewall rule #342 violating Zero-Trust principle

Conversational AI (Agent-Driven)

🤖 Ask: “Why is Delhi branch slow?”