Review what's new and changed, and the fixes and limitations in Document Automation for the v.38 release.

What's new
Azure AI Document Intelligence version 4.0 support in Standard Forms (Service Cloud Case ID: 02166473)

You can now create custom models in Document Automation using Azure AI Document Intelligence version 4.0. The new capabilities include improved custom models, improved accuracy in data extraction, and signature detection.

The following capabilities are included in the Control Room:

  • The Models page now displays the version number used to create each Azure AI Document Intelligence model.
  • Support for signature detection is introduced, enabling identification of handwritten and digital signatures in documents. This improves automation accuracy in workflows that require signature validation.

Create a learning instance for standard forms | Validation rules in Document Automation
Support for new languages in Automation Anywhere user-defined provider

You can now process documents in the following languages for the User-defined document type when using the Automation Anywhere (user-defined) provider and ABBY OCR or Google Vision OCR provider:

  • Czech
  • Danish
  • Finnish
  • Norwegian
  • Slovak
  • Swedish

Languages supported in Document Automation
Fixes
You can now upload and process documents without errors for learning instances.

Previously, an error was displayed in certain scenarios.

Service Cloud Case ID: 02135184, 02135889, 02154359
You can now process the same documents subsequently without errors.

Previously, an error was displayed in the validator in certain scenarios.

Service Cloud Case ID: 02187660
You can now create Standard Forms models without seeing any performance issues.

Previously, users were experiencing performance issues in certain scenarios.

Service Cloud Case ID: 02219164
After training documents using Standard Forms Neural model, the Run analysis option will extract appropriate information from test documents.

Previously, data was not extracted for certain fields.

Service Cloud Case ID: 02185363, 02185363

The validation feedback field in the version history in test mode will only display fields that were validated by users.

Previously, fields extracted using generative AI were displayed in the validation feedback field.
When you have the Test mode enabled and validation feedback disabled for a learning instance, the cluster ID is now displayed correctly for a document processed in test mode.

Previously, incorrect cluster ID was displayed for the processed document in such a scenario.

Limitations

You might see an error during model training in Standard Forms when creating a new model in an existing project after adding a new field.

Workaround: Reload the Projects page before creating a new project. If you create a Projects page without refreshing the page and an error occurs, create a new project after reloading the Projects page and restart the training. Existing learning instances, projects, and models are not affected.
Limitations from previous releases
You will not be able to use a custom table name in Japanese, Korean, or Chinese when creating a custom table.
When you restore a learning instance to any previous version from version history and reprocess a document, the document upload count is increased.
When you process documents with file names greater than or equal to 75 characters in test mode, you might not see improvements in the reprocessing time for such documents.
If you have disabled the OCR provider in the administrator settings and if you are using a language other than English for your Control Room, you will see an error to enable the OCR provider settings in English in the following scenarios:
  • When you create a learning instance that is using an OCR provider
  • When you change the OCR provider for an existing learning instance
When you use the Document Classifier actions (Classify, Classify documents, and Train Classifier) and Extract Data action in the Document Extraction package together in a bot, the bot will fail to execute.

Workaround: Ensure that you create separate bots when using any of the actions from the Document Classifier package and the Extract Data action of the Document Extraction package. If you need to execute these bots in a sequence, include these bots in an Automation Co-Pilot process.
If you copy a learning instance that is using a third-party parser configured in Document Automation and process documents using the copied learning instance, data extraction will fail.
When a user processes a document on a custom process learning instance, the validate document count is not updated post extraction. Also, if the user submits the document, the validate document count is updated with a negative value.
A user with the Automation Co-Pilot administrator permissions is unable to view the Document Automation tasks that are assigned or requested and are in pending or complete status.
When you are using the IQ Bot Pre-processor package actions and if the Output folder path contains Japanese characters, you will see an error when processing documents.

Workaround: Create an output folder in a folder path that does not contain any Japanese characters and provide the path in the output folder path field.