The operational problem
Root-cause analysis is slow when symptoms, telemetry, runbooks, ownership data, and recent changes live in disconnected systems.
What changes for the service
The RCA agent assembles incident context from observability, ITSM, knowledge, and metadata sources, then proposes evidence-backed hypotheses and next diagnostic steps.
How it works in the service
Inside the service
During an incident, evidence from logs, metrics, tickets, ownership data, and knowledge sources is assembled into structured, grounded hypotheses. The agent does not hide uncertainty — it makes the available evidence easier to evaluate and narrows the search.
Why it is delivered this way
Root-cause work stays a human responsibility. RED Reply uses the agent to shorten the orientation phase for its responders, and the accountable engineer decides what the cause is and what happens next.
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
- Incident tickets
- Logs
- Metrics
- Recent changes
- Runbooks
- Ownership metadata
Outputs
- Root-cause hypotheses
- Evidence links
- Diagnostic next steps
- Escalation context
- Incident update draft
Integrations
- ITSM systems
- Monitoring platforms
- Log platforms
- Knowledge base
- Application metadata
How it is built
The pattern is built as an orchestration layer that can call monitoring, log, ticket, and knowledge tools while preserving evidence links and human approval for actions.
