Aditya Anand@adityaanandgzb48907

NetOps AI is a multi-agent, Retrieval-Augmented Generation (RAG) platform designed to automate network incident investigation and accelerate root cause analysis in enterprise networks. The system combines historical incident reports, troubleshooting playbooks, diagnostic outputs, and networking documentation within a ChromaDB-powered knowledge base. When a network alert is received, a Planner Agent analyzes the incident and determines the required investigation steps. A Knowledge Agent retrieves relevant historical incidents and operational guidance, while a Diagnostic Agent collects and analyzes device telemetry and command outputs. The gathered context is then passed to a Review Agent that performs AI-driven root cause analysis and generates evidence-backed findings. Finally, a Decision Agent recommends remediation actions and operational next steps for network engineers. The platform leverages LangGraph to orchestrate collaboration between specialized agents and uses large language models to reason over network data, historical incidents, and troubleshooting procedures. By reducing Mean Time to Resolution (MTTR), improving operational efficiency, and providing explainable recommendations, NetOps AI enables faster and more reliable incident response. The solution is designed as a scalable prototype for modern Network Operations Centers (NOCs), demonstrating how multi-agent AI systems can transform network monitoring, diagnostics, and automated decision support.

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