Reliability / On-call
Self-Healing Incident Response
Detect, diagnose, and remediate production incidents — or escalate with a complete evidence bundle.
The problem
On-call follows a tedious 15–30 minute loop: an alert fires, an engineer checks 3–5 dashboards, classifies the issue, runs a fix, and verifies. It's mechanical, it's 24/7, and transient noise buries the real incidents.
Our approach
A two-tier stack. An AI agent handles judgment — is this real, should we investigate? A deterministic workflow engine handles action — diagnose, remediate, verify — with scoped permissions and full audit logs. Adaptive triggering, safe execution. Destructive steps are single-resource scoped, rate-limited, and dry-run by default.
How it works
Where the AI agent acts, and where a human stays in the loop.
Monitoring alert
A synthetic probe, log alarm, or metric breach posts to the team's messaging app.
AI agent triages
Reads the alert and decides whether action is warranted — a real issue vs a known transient.
Parallel diagnostics
The workflow runs read-only queries across logs, metrics, edge events, and probe history at once.
Classify the incident
The root-cause label drives the next action.
Verify recovery
Re-runs the probe and confirms the service is healthy.
Post outcome & learn
Result posted back to the alert thread; fed into the agent's memory for next time.
Want something like this for your team?
We'll find one workflow worth automating and the ROI behind it. No slides.