AI-powered Root Cause Analysis (RCA) system built with n8n and OpenAI to automate operational routing, generate leadership intelligence, and create a closed-loop feedback system for continuous improvement.
Support teams don’t just need to resolve tickets — they need to understand why issues are happening and how to act on them.
In most organizations:
- RCA is fragmented or manual
- Trends are identified too late
- Operational follow-through is inconsistent
- Leadership lacks clear, actionable insights
This project introduces an AI-powered RCA Operating Model that connects:
- Operational execution (task routing)
- Strategic intelligence (trend analysis & reporting)
The result is a system that not only identifies root causes — but acts on them and continuously improves over time.
This is Project 7 in a broader system:
- Project 1 → AI Ticket Triage
- Project 2 → Escalation Risk Detection
- Project 3 → SLA Breach Prediction
- Project 4 → Weekly Support Intelligence Report
- Project 5 → AI Response Suggestion
- Project 6 → AI Support RCA Engine
- Project 7 → AI RCA Operating Model (this project)
This system introduces a dual-flow operating model:
- Flow 1 → Operational RCA Routing
- Flow 2 → RCA Intelligence & Reporting
Together, they create a closed-loop system where insights directly influence operational actions.
This project builds on a multi-stage AI-powered support system designed to evolve teams from reactive support to intelligence-driven operations.
Classifies incoming support tickets and structures data for downstream workflows.
👉 https://github.com/jesseautomates/ai-support-ticket-triage-automation
Identifies tickets likely to escalate using AI signals.
👉 https://github.com/jesseautomates/ai-support-escalation-risk-detection
Predicts SLA risk before deadlines are missed.
👉 https://github.com/jesseautomates/ai-sla-breach-prediction
Generates structured leadership insights from support data.
👉 https://github.com/jesseautomates/ai-support-intelligence-report/
Generates context-aware responses to assist agents.
👉 https://github.com/jesseautomates/ai-support-response-suggestion
Identifies root causes and separates known vs unknown issues.
👉 https://github.com/jesseautomates/ai-support-rca-engine
Transforms RCA insights into operational actions and leadership intelligence.
Together, these projects form a layered system:
Triage → Risk Detection → SLA Prediction → Intelligence → Agent Assistance → RCA → Operational Execution
- Routes RCA-driven work to the correct teams automatically
- Classifies issues into operational action buckets
- Generates weekly RCA intelligence reports for leadership
- Combines deterministic metrics with AI-generated insights
- Identifies risks, improvements, and emerging issues
- Creates a feedback loop between insights and operations
- Reduces manual triage and improves prioritization
- Pulls structured RCA dataset (Google Sheets / ticket system)
- Serves as the single source of truth for issue trends
- Assigns each RCA to an action category:
- Engineering
- Knowledge Base
- Automation
- Monitoring
- Applies rules to determine the correct action path
- Translates RCA insights into operational decisions
Triggers execution based on RCA type:
- Engineering → Create engineering task
- Knowledge → Create KB / enablement task
- Automation → Create automation opportunity
- Monitoring → Notify support team
- Tasks are created or alerts are sent automatically
- Eliminates manual triage and routing
- Normalizes RCA dataset
- Calculates week-over-week changes
- Applies priority flags
- Condenses RCA data into a summary payload
- Prepares inputs for both analytics and AI
- KPI generation:
- Total RCAs
- High priority issues
- New issues
- Resolved issues
- Trend shifts
- LLM generates:
- Executive summary
- Top risks
- Improvements
- Emerging issues
- Leadership recommendations
- Cleans and parses structured AI output
- Merges AI insights with KPI data
- Sends formatted HTML report via email
- Provides clear, actionable intelligence
The most important system design element:
Insights → Operational Feedback Loop
- Intelligence feeds directly back into RCA routing
- Ensures:
- High-risk issues are prioritized
- Improvements are reinforced
- New issues are monitored early
This transforms RCA from a reporting exercise into an operational driver.
- Executive Summary
- Top Risks
- Top Improvements
- New Issues
- Recommendations
- Engineering tickets
- Knowledge base updates
- Automation opportunities
- Support alerts
- n8n (workflow orchestration)
- OpenAI API (analysis + insight generation)
- Google Sheets (data source + logging)
- Email integrations (Gmail / SMTP)
- Import workflow JSON into n8n
- Connect Google Sheets dataset
- Configure OpenAI credentials
- Define RCA categories and routing logic
- Set up email delivery node
- Test with sample RCA dataset
- Iterate on prompts and thresholds
- Demonstrates end-to-end RCA operationalization
- Connects data → insight → action
- Combines rules-based systems with AI reasoning
- Enables proactive support operations
- Introduces a closed-loop improvement system
Most teams stop at identifying problems.
This system shows how to:
Turn root cause insights into real operational change.