Wireless Optimization - Use Cases

Enterprise IT / Wireless

Wireless Optimization: Proactive Channel Switching

Predict spectrum degradation before users notice and orchestrate graceful channel switches with zero service disruption.

Fewer Incidents

Prediction Accuracy

Autonomous

$0K

Saved

Challenge

Spectrum interference causes unpredictable degradation
Reactive controllers respond only after users complain
Manual channel tuning is too slow for dynamic environments
45-minute average response to interference events

Solution

ML models forecast channel health and identify clean alternatives while agentic proactive switching handles customer-impact evaluation and safety guardrails — predictive and agentic working in cohesion.

Predictive ML Agentic Workflow

1 Telemetry Collection

2 Pattern Learning

3 Degradation Forecasting

4 Clean Channel ID

5 Customer Evaluation

6 Guardrail Validation

7 Switch Orchestration

8 Auto vs Manual Decision

9 Outcome Tracking

Results

67%

Fewer incidents

45%

Fewer complaints

+18%

Throughput improvement

92%

Prediction accuracy

$380K

Annual savings

Why Multi-Method Matters Here

ML PredictsForecasts degradation before it impacts users

Rules Enforce SafetyGuardrails prevent switches during critical operations

Workflows OrchestrateMulti-step validation ensures graceful transitions

LLMs ExplainGenerate human-readable reports for NOC review

Wireless Optimization: Proactive Channel Switching

Challenge

Solution

Results

Why Multi-Method Matters Here

Deploy in 4 Weeks. See Results in 60 Days.