As an IT Infrastructure Manager, I want AI-powered predictive analytics and intelligent anomaly detection integrated directly into PRTG so that I can proactively prevent outages, reduce troubleshooting time, and provide executive-level insights on infrastructure health without needing to manually analyze complex monitoring data.

Key Benefits:

• Anomaly detection:
  
  Use AI models to identify unusual traffic patterns, latency spikes, or device behavior that may indicate security threats or system failures.

• Predictive Analytics:
  
  Forecast potential outages or performance degradation based on historical data trends, enabling preemptive action.

• Automated Root Cause Analysis:
  AI can correlate alerts across sensors and logs to suggest likely causes, reducing troubleshooting time.

• Smart Alerting:
  
  Reduce alert fatigue by using AI to prioritize and suppress non-critical alerts based on context and historical resolution patterns.

• Natural Language Interface:
  
  Enable users to query system status or generate reports using conversational language (e.g., “Show me bandwidth usage for the last 7 days”).

Suggested implementation:

• Integrate with existing machine learning platforms or offer built-in models trained on network telemetry.
• Provide APIs for custom AI workflows.
• Offer a dashboard module for AI-driven insights and recommendations.

Use cases:

• Detecting DDoS attacks or rogue devices in real time.
• Forecasting bandwidth saturation during peak hours.
• Automatically recommending sensor configurations based on network topology.