AI agent for handling KSeF errors: retry, alerts, escalations
How to build an AI agent that supports the team in quickly closing errors and process exceptions.
The role of the AI agent in the process
The AI agent does not replace retry policy or business rules. His task is to prioritize, recommend actions and support the operator in handling incidents.
A well-designed agent shortens response time and reduces the number of cases that are escalated without preliminary analysis.
- •Categorizing errors by impact.
- •Suggestion of a corrective path.
- •Automatic creation of a ticket to the appropriate team.
Retros and escalations
Not every error requires immediate human intervention. The agent can distinguish between temporary and permanent errors and trigger the appropriate retry strategy.
For persistent errors, the agent should initiate escalation with a complete context: document, reason, attempt history and recommendation.
- •Retry for temporary errors.
- •Escalation for persistent errors.
- •Full context of the incident in the report.
Efficiency measures
The effect of an agent's work can be measured by MTTR, the percentage of incidents closed without escalation and the stability of the error rate over time.
If the agent does not improve these metrics, the rules or input quality need to be redesigned.
- •MTTR and first reaction time.
- •Percentage of closures without escalation.
- •Trend of repeatable errors.