Learn how to extract selected information from invoices#
Define AI model structure#
Setup the following structure in your project to extract basic invoice information, vendor information and detailed line item information from invoices. Feel free to change the proposed scope of the Label Sets and Labels in this tutorial.
* Use the multi Label Set option when creating the Label Set.
Train the first version of your invoice AI model#
Annotate all documents according to your defined AI model structure using the SmartView.
Review our Improve Extraction AI checklist.
Retrain or reevaluate your Invoice AI#
After you have trained your Extraction AI, you can start retraining the AI to increase its accuracy. Each retraining process improves the accuracy of your model.
Upload other documents than the ones you already uploaded
Once the OCR process has been completed, Feedback required via the SmartView to every yellow marked Annotation.
Now you have two options:
if you add the document to the Status: Training documents you will provide more data to the AI to learn. If you don’t change the number of documents with the Status: Training documents you will probably see that the accuracy of your model will improve.
if you add the document as Status: Test documents you will provide more data to test the AI on. If you don’t change the number of document in Status: Training documents you will probably see that the accuracy of your model will drop.
What happens if the accuracy of the model decreases after retraining?
You will get full access to the model and the evaluation. However, only the best model will be used via API. The accuracy for all models can be updated via admin action using the latest Test data.
Use AI model#
As soon you are confident about the results, you can use your AI via our Integrations & API. The API of the project is available since the project has been created.