AI-Native QA Pipeline for Atlassian Ecosystem

A lean QA automation layer built on top of Jira Service Management for a 30-agent service desk — using only native tools: Rovo, Jira Automation, and Confluence.

The system samples tickets automatically each week across three modes (random, stratified, and targeted), pipes them through a custom Rovo agent trained on the team's QA scorecard, and routes outcomes into structured Confluence records and JWM tasks based on score thresholds. No dedicated QA analyst required. Humans stay in the loop for judgment calls — the automation handles the volume, consistency, and paper trail. Delivered measurable results in 30 days: full coverage on high-priority tickets, feedback cycle cut from 6 days to 2, and 7 new KB articles surfaced from systemic issue detection.