Wired Assurance
Extend Mist AI capabilities to your wired infrastructure with intelligent switch management, automated port profiling, proactive cable diagnostics, and anomaly detection.
AI-Driven Switch Management
| Feature | AI Capability | Operational Benefit |
|---|---|---|
| Port Profiling | ML classifies connected devices and auto-assigns VLANs | Zero-touch port configuration |
| Cable Testing | AI-assisted TDR diagnostics with fault location | Pinpoint cable issues without physical testing |
| Topology Discovery | Automatic L2/L3 topology mapping with AI validation | Accurate, always-current network diagrams |
| Anomaly Detection | ML baselines per-port traffic and flags deviations | Early detection of broadcast storms, loops |
Wired SLE Framework
Switch Health
AI monitors CPU, memory, temperature, and fan status across all managed switches, predicting hardware failures before they impact the network.
Port Availability
Tracks port utilization, error rates, and flapping patterns. AI identifies ports with degrading performance that indicate cable or hardware issues.
PoE Assurance
Monitors Power over Ethernet delivery, detecting devices that draw excessive power, PoE negotiation failures, and power budget approaching capacity.
Configuration Compliance
AI validates switch configurations against defined templates and best practices, flagging drift and unauthorized changes in real time.
Wired-Wireless Correlation
End-to-End Visibility
Mist AI traces client connectivity from wireless AP through switch ports to the distribution layer, providing full-path troubleshooting.
Cross-Domain Root Cause
When wireless clients experience issues, Marvis checks if the root cause is actually in the wired infrastructure: uplink errors, VLAN misconfigurations, or spanning tree problems.
Unified Configuration
Manage wireless and wired policies from the same dashboard with consistent AI-driven insights across both domains.
Impact Analysis
AI quantifies how switch issues affect wireless service, helping prioritize remediation based on total user impact across both domains.
Lilly Tech Systems