AI Assistant Root Cause Analysis for Network Issue Remediation
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Solution Overview
Problem
Network issues in personal and professional environments often lead to connectivity disruptions, slow speeds, or outages, necessitating time-consuming IT ticket processes for resolution, which can be inefficient for complex problems affecting multiple users.
Innovation Solution
A digital experience AI assistant that employs an AI agent with an LLM, memory module, planner component, and tools to troubleshoot device issues, perform root cause analysis, and provide remediation recommendations, using a device-specific QR code for authentication and authorization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional IT ticket processes are used to resolve network issues, then users can report problems formally, but the resolution process becomes time-consuming and inefficient
Solution Approach 1:
The patent implements an AI agent that enables users to self-diagnose and self-resolve network issues through automated interactions. The agent collects device metrics, performs root cause analysis, and provides remediation recommendations without requiring manual IT intervention for every issue, thus reducing ticket handling time while maintaining resolution effectiveness
Solution Approach 2:
The system performs preliminary diagnostics and root cause analysis automatically when issues are detected or reported. By pre-collecting device metrics and analyzing potential causes before full IT intervention is needed, the system accelerates the initial response phase while preserving thoroughness for complex issues
2Measurement precision
If manual troubleshooting processes are used for complex network issues, then detailed analysis can be performed, but the process becomes inefficient when multiple users are affected
Solution Approach 1:
The AI agent is designed to handle multiple types of network issues across different devices and users through a unified platform. It can simultaneously diagnose connectivity problems, performance issues, and configuration errors, providing scalable support that maintains diagnostic accuracy while improving efficiency for multi-user scenarios
Solution Approach 2:
The system implements continuous feedback loops where device metrics are collected, analyzed, and used to refine diagnostic accuracy. The AI agent learns from resolution outcomes and metric patterns, improving its ability to accurately diagnose issues while maintaining high throughput for multiple concurrent cases
Data Source
AI summary
Systems and methods for an Artificial Intelligence (AI) agent adapted to support end users includes performing monitoring of one or more users via a cloud-based system and logging device metrics based thereon, wherein the device metrics are associated with one or more devices of the one or more users; providing an Artificial Intelligence (AI) agent adapted to troubleshoot issues related to the one or more devices; and responsive to the AI agent being invoked by a user of the one or more users, providing one or more remediation recommendations for one or more issues based on the device metrics.