The operational problem
L2 and L3 engineers spend too much time reconstructing ticket history, searching previous incidents, drafting updates, and converting resolution knowledge into documentation.
What changes for the service
The agent reads the active ticket, retrieves related knowledge and past issues, generates summaries and response drafts, proposes RCA context, and can create reusable documentation.
How it works in the service
Inside the service
Engineers stay in Jira Service Management and get the preparation work done for them: the incident summarised, related knowledge retrieved, prior similar tickets surfaced, and a first response drafted. The engineer reviews, corrects, and decides.
Why it is delivered this way
Handling time falls because the context arrives with the ticket instead of being assembled by hand for every case. RED Reply remains accountable for the resolution and for the quality of what reaches the customer; expert judgement is never delegated to the automation.
Accountable delivery
This capability is not sold as a product. RED Reply operates it as part of a managed service, with named service roles responsible for quality, escalation, and outcomes. Automated steps are scoped, logged, and reversible, and the actions that change a system or reach a customer stay under human control.
What it uses and produces
Inputs
- Jira incidents
- Ticket comments
- Ticket history
- Confluence pages
- Similar issues
- Service metadata
Outputs
- Ticket summaries
- RCA suggestions
- Customer response drafts
- Internal updates
- Confluence documentation
Integrations
- Jira Service Management
- Confluence
- Identity provider
- Agent runtime
- Observability stack
How it is built
The pattern keeps the agent inside the ITSM workflow, using tool calls for Jira and Confluence actions while maintaining controlled execution and traceable outputs.
