Diagnose incidents — don’t just track them.
Every critical incident gets an AI investigation that reads your past incidents, recent deploys, and Sentry errors — surfacing confidence-scored root-cause Findings and proposing the next action for a human to approve.
Every critical incident gets investigated
The moment a critical incident opens — even a machine-opened 3am page — scaling.cloud runs an investigation and posts confidence-scored Findings with the evidence behind each one. You confirm or dismiss with a click.
- Auto-runs on critical incidents, however they were opened
- Confidence-scored Findings with linked evidence
- Confirm or dismiss each Finding — the AI never acts on its own
It knows what changed, and why
Findings are drawn from the signals you already produce. Past resolved incidents are matched by symptom, GitHub deploys and merges are correlated to the incident timeline, and Sentry stack traces are read for root cause.
- Similar past incidents matched by symptom
- GitHub deploys and PRs correlated as suspect changes
- Sentry stack traces and suspect commits as root-cause Findings
Surfaced where you work, acted on with approval
Tag @scaling in the incident channel for a live summary, start your retro from a seeded post-mortem draft, and let Findings propose the next Action — every one human-approved. Add declarative when → then rules to automate the routine.
- @scaling summaries in Slack and Teams
- Post-mortem drafts seeded from Findings
- AI-proposed Actions and when → then Automation Rules
Make this part of your response playbook.
Join the engineering teams who already rely on scaling.cloud for every incident.