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Jira Automation

Business Need​

Automatically respond to Jira tickets by consulting technical documentation in Confluence, providing accurate solutions and reducing the burden on development and support teams while maintaining consistent response quality.

Solution Overview​

This solution leverages AI Workflows with Confluence and Jira integration to deliver intelligent ticket automation:

Step 1: Documentation Knowledge Base

  • Data Source: Technical documentation, API references, troubleshooting guides, and architecture diagrams stored in Confluence
  • Document Retriever: Vector store created from 1,800+ Confluence pages across engineering documentation spaces
  • Content Coverage: System architecture, deployment guides, API documentation, known issues, and troubleshooting runbooks
  • Maintenance: Documentation is continuously synced as engineers update Confluence pages

Step 2: Jira Integration & Ticket Processing

The AI Workflow integrates directly with Jira:

  • We are leveraging Jira Automation to invoke the AI workflow with relevant information about the ticket context and user queries.
  • AI Workflow responds and this is logged in the ticket
  • Follow-up questions and conversations on the ticket are also sent to the AI Workflow for further processing.
💡Pro Tip

Create ticket templates that prompt users to include specific information (error messages, steps to reproduce, environment details). The AI Workflow can extract this structured data more accurately, leading to better responses.

Step 3: Documentation Search & Response Generation

The workflow performs intelligent documentation retrieval:

  • Queries the Confluence document retriever using semantic search
  • Identifies the most relevant documentation sections, code examples, and troubleshooting steps
  • Synthesizes information into a clear, actionable Jira comment
  • Includes links to relevant Confluence pages for deeper exploration
  • Tags ticket with relevant labels (e.g., "auto-resolved", "needs-verification")

Step 4: Response Posting & Follow-up

  • Posts detailed response as a Jira comment within 60-90 seconds
  • Monitors for follow-up comments from ticket creator
  • Can engage in multi-turn conversation to clarify or provide additional guidance
  • Escalates to human team if issue remains unresolved after 2-3 interactions

How It's Used in Practice​

This solution operates as an automated first-line support system for technical tickets.

The system has processed hundreds of Jira tickets over 9 months, with 40% marked as resolved based on AI-provided documentation references.

✨Key Outcomes

Key achievements:

🚀 40% of tickets resolved with documentation references​

Developers and customers find answers without engineering team involvement

⚡ 1.5-minute average response time​

Immediate guidance instead of waiting hours or days for engineering response

📚 Identified documentation gaps​

Recurring questions without good answers highlight areas needing better documentation

Additional Information​