Inovai / Use cases
A process error is found too late.
AI watches for deviations and alerts you before a loss occurs.
Problem
The exception shows up only once it costs time, material or money.
What we’ll do
Rules and models over operational data, alerts to the responsible person.
Result
The responsible person gets an alert, including the cause.
How it works
Four steps; a person decides on escalation.
Production
Step 1Process eventsTransactions, logs, MES, ERP and inspection records.Scrap rate
Step 2Deviation detectionRules, thresholds and combinations outside the normal pattern.Batch 2611+8% scrapSupplier BmonitorLine 2within limits
Step 3Context and priorityWhat happened before, who the owner is and what the impact is.1exception to resolve
Step 4Next stepA task or escalation with the material ready.Verified by a humanWhat changes
Early detectionThe deviation is dealt with before it becomes a loss.
Fewer false escalationsOnly real cases go to the expert.
Learning from repeated errorsPatterns are recorded and caught earlier next time.
When it makes sense
It pays off when
- Production and logistics, where a deviation means a defective part or a delay
- Finance: suspicious transactions and anomalies in flows
- Service: repeated complaints and problem accounts
What to watch out for
- Without good thresholds, users are flooded with false alarms
- Without data history, the explanation will be weak
- AI suggests the priority; a person decides on escalation