Every insight becomes an actionable case
Detected anomalies don't just appear as alerts — they become cases on your AI Kanban board. Organized by category, ranked by severity, with confidence scores and recommended actions. The board stays clean through automatic TTL-based archiving.
No alert fatigue. No manual cleanup. Just actionable work, organized.
From detection to action, organized
Traditional alerting gives you a stream of notifications. You have to decide what's important, track what you've addressed, and remember to follow up. That's operational overhead.
The AI Kanban transforms alerts into a managed workflow. Cases appear, get worked, and auto-archive when resolved or expired. Your attention goes where it matters.
Rule-based detection + AI pattern analysis
Cases come from two complementary sources — both feeding into the same unified Kanban board.
Computed Insights
Rule-BasedSeven specialized detectors run every 30 minutes. When metrics cross thresholds or deviate from baselines, they generate computed insights with deterministic severity.
- Threshold-based detection
- Day-over-day comparison
- Fingerprint deduplication
- Immediate case creation
computed_insights
AI Insights
Engagor AIEngagor AI analyzes aggregated data looking for patterns humans might miss — correlations across dimensions, emerging trends, and subtle anomalies that don't fit simple threshold rules.
- Cross-dimensional patterns
- Trend identification
- Natural language explanations
- Confidence scoring
ai_insights
Everything you need to act
Gmail Soft Bounce Spike
Soft bounces increased 340% vs baseline. Rate limiting detected across 3 sender identities. Pattern consistent with reputation throttling.
Reduce Gmail volume by 30% for 7 days. Monitor complaint rate closely.
Severity + Confidence
Visual priority ranking plus AI confidence score (0-100%).
Title + Description
Clear summary and detailed explanation of the finding.
Context Tags
ISP, identity, category — quick filtering and context.
Recommendation
Actionable next step generated by Engagor AI.
TTL + Actions
Time remaining before auto-archive, plus quick actions.
Automatic prioritization
Cases are automatically categorized by severity. Each level has its own TTL — critical issues stay visible longer, informational items expire quickly.
Immediate attention required. Reputation at risk, delivery severely impacted, or threshold breach.
Example: Complaint rate >0.10%, bounce spike 5x
Should investigate soon. Trending toward problems or moderate deviation from baseline.
Example: Deferral rate >5%, engagement -15%
Informational observation. Notable pattern but not urgent. Good to know.
Example: Volume +/-30%, device mix shift
Positive observation. Good performance, improvement trend, or resolved issue.
Example: Bounce rate normalized, engagement +20%
Auto-archive keeps it clean
Alert fatigue kills productivity. Stale cases clutter the board. Manual cleanup is tedious. The AI Kanban solves this with automatic lifecycle management.
TTL Expiration
Each case has a time-to-live based on severity. When it expires without re-detection, it auto-archives.
Auto-Resolution
If the underlying issue resolves naturally (metric returns to baseline), the case moves to auto-resolved.
Manual Dismiss
Acknowledged an issue? Dismiss it to archive immediately. One click, it's gone.
Fingerprint Dedup
Same issue detected again? Existing case refreshes its TTL instead of creating duplicates.
"Talk about this issue"
Every case card has a direct link to AI Studio. Click it, and your conversational AI opens with full context — the anomaly details, the metrics, the history. Ask follow-up questions, drill deeper, get recommendations.
No copy-pasting data. No explaining the situation. The AI already knows.
Ready for organized email operations?
See how the AI Kanban can transform your workflow from reactive firefighting to proactive management.