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HN837: Agentic AI to Reduce MTTR

Ethan Banks and Eduard Dulharu discuss at AutoCon 5 how agentic AI can decrease Mean Time to Recovery (MTTR) in complex networks by using deterministic workflows and customized models for telemetry analysis and solution proposals.

MAIN POINTS
  1. Agentic AI helps reduce MTTR in complex network environments.
  2. AI agents utilize deterministic workflows for efficient problem-solving.
  3. Custom fine-tuned models are used to analyze network telemetry.
  4. Solutions are proposed based on AI analysis to improve recovery times.
TAKEAWAYS
  1. Implementing agentic AI can significantly enhance network recovery efficiency.
  2. Deterministic workflows ensure consistent and reliable AI-driven solutions.
  3. Fine-tuning models is crucial for accurate telemetry analysis.
  4. Proactive AI solutions can minimize downtime and improve network performance.
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