Autonomous AI Agents & Operational Triage
Smarter Systems for Triage & SLA Performance
Proper intake and precise diagnostic triage do more than streamline internal operations they directly protect client retention and SLA commitments. Misrouted tickets, missing error payloads, and delayed initial assessments frustrate customers and waste critical engineering hours. Explore how autonomous Atlassian agents, custom Forge applications, and generative AI Workspace plugins streamline request intake, extract key diagnostics, and accelerate triage across Slack, Gmail, and Jira.
Gmail to Jira Integration with Gemini & Google Workspace Plugin
Problem: Customer escalation emails in Gmail required manual copying, parsing of error dumps, and repetitive back-and-forth to convert into engineering tickets.
Solution: Engineered a Google Workspace add-on utilizing generative AI to parse incoming email threads, summarize key technical issues, and generate formatted Jira tickets with relevant metadata.
Slack to Jira Integration with Atlassian Rovo
Problem: Support inquiries inside Slack channels arrived missing reproduction steps, logs, and context, forcing engineers into long back-and-forth threads before manual ticket creation.
Solution: Configured an Atlassian Rovo agent in Slack that prompts users in-thread for required system metadata, extracts diagnostic details, and automatically provisions structured Jira issues.
Native Jira Cloud Triage & Diagnostic App using Atlassian Forge
Problem: High intake queues sat unassigned while engineers spent excessive time searching fragmented Confluence runbooks to diagnose recurring errors.
Solution: Developed a custom serverless Forge app that analyzes unassigned ticket queues, auto-applies taxonomic labels, routes to the right squad, and surfaces grounded Confluence runbooks directly on the issue canvas.
