Self-learning AI in DII
The self-learning AI feature enhances the DII workflow by learning from user corrections made during invoice validation. When the RPA bot automatically loads invoice data and exceptions occur, for example, when Vendor, Company, or AOC values are missing or incorrect, the user manually updates the DII. These corrections are captured, stored in log tables, and used to improve future AI predictions.
Logging framework
| Area | Description |
|---|---|
| Log storage |
The system maintains dedicated log tables to track extracted and edited values:
|
| Logging rules |
|
Activation
Self-learning AI activates when user edits reach the hyper parameter threshold count defined during AI model deployment.
If no matching record is found using self-learned data, the system falls back to Normal AI logic.
See AI models.
This table shows the list of learning scenarios and inputs.
| Learning type | When learning is triggered? | What AI captures? | Inputs used |
|---|---|---|---|
| Vendor learning |
|
Final user-corrected vendor |
|
| Company learning |
|
Corrected Company value |
|
| Add-on charge (AOC) code learning |
|
Final user-entered AOC code |
|