IncOv / Incident intelligence
Applied AI / Under validation
Turn every incident into better judgment.
Match live signals with reviewed knowledge. Keep a human in control.
- 01Incident detectedHigh error rate on checkout serviceP1
- 023 related signalsError spike · latency breach · timeout clusterGrouped
- 03Matched runbookPayment gateway timeoutsSource reviewed
- 04Review requiredRecommendation is boundedHuman check
- 05ApprovedDecision recordedResolved
01 / The gap
The fix exists. The context is scattered.
IncOv turns reviewed incident knowledge into reusable decision support.
Noisy signals
→Trusted context
- 01IntakeCapture the incident.
- 02GroupConnect related signals.
- 03MatchFind reviewed knowledge.
- 04AssessBound the recommendation.
- 05ApproveKeep ownership human.
02 / What it reuses
Resolution knowledge that compounds.
- IncidentsNormalize approved operational inputs.
- Resolution PacksReuse reviewed SME knowledge.
- EvidenceKeep the reasoning inspectable.
- ApprovalStop at the human decision boundary.
Less guessing. More reviewed context.
Evidence trail
AI recommends. People decide.
The recommendation, reviewed evidence, and named approval point remain visible.
RecommendationReview requiredApply mitigation from reviewed knowledge
Evidence3 related signalsReviewed runbook attached
ApproverNamed ownerHuman review recorded
Status: approved✓Decision recorded
03 / Current boundary
Under validation. Built to be reviewed.
The workflow is public. Measured production outcomes are not claimed.
What does IncOv ingest?
Approved incident inputs that can be normalized into the review workflow.
How is knowledge matched?
Against reviewed Resolution Packs before bounded AI assessment.
Where does approval happen?
At the human policy gate before any external action.
What is validated today?
The public walkthrough shows the intended workflow and controls, not a measured production outcome.