Lilly Tech Systems
AI Chatbot for Network Troubleshooting
Learn to build intelligent chatbots that help network operations teams troubleshoot issues faster. From architecture design and knowledge base creation to Slack/Teams integration, build a chatbot that queries monitoring systems, analyzes data, and provides actionable diagnostics.
What You'll Learn
Build production-ready AI chatbots for network operations teams.
Chatbot Architecture
Design scalable chatbot systems with RAG, function calling, and multi-step reasoning for network diagnostics.
Knowledge Base
Build a network-specific knowledge base from runbooks, documentation, and historical incident data.
Live Diagnostics
Connect your chatbot to monitoring tools for real-time device queries and health checks.
Slack/Teams Integration
Deploy your chatbot into team collaboration platforms for seamless NOC operations.
Course Lessons
Follow the lessons in order or jump to any topic you need.
1. Introduction
Why AI chatbots for networking, use cases, and the value proposition for NOC teams and network engineers.
2. Architecture
Design patterns for network chatbots: RAG, function calling, agent loops, and conversation management.
3. Knowledge Base
Build and maintain a knowledge base from runbooks, vendor docs, incident history, and network documentation.
4. Diagnostics
Connect the chatbot to live network devices and monitoring systems for real-time troubleshooting.
5. Integration (Slack/Teams)
Deploy your chatbot into Slack, Microsoft Teams, or custom web interfaces for team collaboration.
6. Best Practices
Security, access control, conversation design, monitoring, and continuous improvement strategies.
Prerequisites
- Basic understanding of chatbot concepts and APIs
- Familiarity with Python and REST APIs
- Access to an LLM API (OpenAI, Anthropic, or similar)
- Understanding of network monitoring tools (Prometheus, Zabbix, etc.)