Exceptions are addressed too late
An error is found only when it already costs time or money.
Use case 03
Exception analysis
Exception analysis
in processes
The workflow watches for recurring errors, non-standard values and situations outside the expected course. Instead of another report, it prepares the reason, the priority and the next step.
Where the problem arises
What slows the process down today
Five typical points that together steal time, quality and trust in the outputs. If you recognise any of these, the workflow has somewhere to start.
Reporting warns but doesn't explain
The dashboard shows an anomaly, but not the reason or the priority.
Repeated errors with no lessons learned
The same type of problem comes back - the process doesn't catch it.
Escalation without context
The responsible role gets a warning without the data it needs.
Dependence on one expert
Only a few people can find and explain exceptions - the workflow rests on them.
Step by step in one flow
The workflow doesn't just read documents or only show numbers. It connects data, rules and decision points into a single flow with a clear output.
Loads events from the process
Logs, transactions, MES, ERP, control records.
Detects deviations
Rules, thresholds and model-based detection of combinations outside the norm.
Adds context
What happened before, which data is related, who the owner is.
Classifies and prioritises
Severity HIGH/MEDIUM/LOW + a category by business impact.
Prepares the next step
A recommendation, an escalation, a ticket or a task with the context already in place.
What changes in operations
The concrete impact on work
The goal isn't to deploy AI. The goal is to give people back time to decide and free the process from depending on a handful of experts.
Early detection
The workflow finds the error before it escalates into a loss.
Fewer escalations without a reason
Only real cases reach the expert.
Traceable history
What happened, how it was assessed, who handled it.
Learning from repeated errors
Error patterns are recorded - the workflow catches them earlier next time.
When it makes sense to start
Three typical situations
A workflow doesn't bring the same value everywhere. Here are three scenarios where it pays to start.
Manufacturing and logistics
Where a deviation means a defective part or a delay.
Finance and accounting
Suspicious transactions, anomalies in cash flows.
Customer service
Recurring complaints, escalations, problem accounts.
What to watch out for
Limits we state up front
Three risks we recommend addressing already at the design stage - not later in operations, where they cost time and trust.
Noisy alerts
Without good thresholds the workflow floods users with false positives.
Context rests on data
If the source data has no history, the explanation will be weak.
Human validation stays
AI suggests the priority - the final decision on escalation stays with a person.