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Arooj Javed
Arooj Javed

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My Journey Building AI Ticket Routing & SLA Breach Prediction in JIRA (With Code)

Project Overview

In today’s support-heavy environments, reducing ticket handling time and meeting SLA targets are critical metrics. I recently led an internal automation project where I implemented an AI-based solution in JIRA to route support tickets intelligently and predict SLA breaches — all without paid plugins or external tools.

📌 The solution uses JIRA’s native automation, external API integration with a Python model, and historical ticket data to streamline routing and resolution workflows.

🎯 Why I Built This

Manual triage was eating up hours every week in our support process. I wanted to explore how AI could help classify incoming tickets based on priority, urgency, and past behavior while also giving the support team SLA breach predictions before they happen.

This project was born out of a real operational challenge, and the results were transformative.

⚙️ Tech Stack
• JIRA Automation (native tools, webhooks)
• Python (Flask API for predictions)
• Pandas & Scikit-learn (for ticket analysis)
• GitHub Actions (basic CI)
• Markdown + Blog publication on Hashnode

📊 Key Outcomes
• 34% reduction in average triage time
• 50% improvement in SLA compliance
• Ticket escalation routing now takes <1 second

Our support team was able to focus on resolutions instead of repetitive tasks.

🧠 How It Works
• Tickets are automatically tagged using past data + keyword mapping
• A lightweight Python model runs in the background and scores urgency
• Based on urgency + ticket type, JIRA routes to appropriate teams
• SLA breach likelihood is calculated and added as a label for visibility

You can view the code, logic, and sample data right here:
🔗 GitHub: https://github.com/aroojjaved93/AI-Powered-Ticket-Routing-SLA-Breach-Prediction-in-JIRA

📷 Screenshots Preview
• AI-based routing workflow
• SLA compliance dashboard
• Prediction output with labels and classifications

(You’ll find the full visuals in the repo README)

✍️ More In-Depth Write-Up

For a full breakdown with diagrams, insights, and practical use cases, check out the blog post here:
📖 Hashnode Blog: https://aisupport.hashnode.dev/ai-powered-ticket-routing-and-sla-breach-prediction-in-support-teams

🙌 What’s Next?

I’m working on expanding the logic to sync with Notion and Slack, building a live alerting system for predicted SLA breaches and delayed responses.

Let me know what challenges you’re solving in your DevOps or support automation setups. I’d love to connect and exchange ideas.

🛠️ Built by: Arooj Javed
🔗 GitHub: @aroojjaved93
💡 Blog: Hashnode @aisupport

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