Dashboards show you what happened. They don't tell you what to do.
Every organization has dashboards. Most dashboards show a red number and then require a human to investigate why it's red, what caused it, what it affects downstream, and what to do about it. That investigation takes hours. By the time someone acts, the problem has compounded.
AI that diagnoses and prescribes.
IntelliFabric's AI layer continuously monitors your operational KPIs and applies predictive models trained on your historical data. When a metric deviates from expected range, the system identifies the most likely root cause, estimates downstream impact, and surfaces a recommended action — automatically.
From connection to insight in four steps.
Baseline learning
During onboarding, IntelliFabric's models learn your normal operational patterns — seasonal cycles, shift patterns, day-of-week variance, promotional effects. This baseline is what anomaly detection compares against.
Continuous monitoring
Every KPI is monitored in real time against its expected range. Deviations that exceed configurable confidence thresholds trigger the diagnostic engine.
Root-cause analysis
The diagnostic engine traces the anomaly backward through the data model — identifying which upstream variable most strongly correlates with the deviation. Line B throughput drop → upstream: tooling change at 14:30. Revenue dip → upstream: cart abandonment spike on mobile.
Recommended action delivery
A specific, actionable recommendation is routed to the right person with full context: what happened, why it happened, what it will cost if unaddressed, and what to do. Delivered via dashboard alert, email, or Teams notification.