- Overview
- Getting started
- Building models
- Consuming models
- Model Details
- 1040 - ML package
- 1040 Schedule C - ML package
- 1040 Schedule D - ML package
- 1040 Schedule E - ML package
- 1040x - ML package
- 3949a - ML package
- 4506T - ML package
- 709 - ML package
- 941x - ML package
- 9465 - ML package
- ACORD125 - ML package
- ACORD126 - ML package
- ACORD131 - ML package
- ACORD140 - ML package
- ACORD25 - ML package
- Bank Statements - ML package
- Bills Of Lading - ML package
- Certificate of Incorporation - ML package
- Certificate of Origin - ML package
- Checks - ML package
- Children Product Certificate - ML package
- CMS 1500 - ML package
- EU Declaration of Conformity - ML package
- Financial Statements - ML package
- FM1003 - ML package
- I9 - ML package
- ID Cards - ML package
- Invoices - ML package
- Invoices Australia - ML package
- Invoices China - ML package
- Invoices Hebrew - ML package
- Invoices India - ML package
- Invoices Japan - ML package
- Invoices Shipping - ML package
- Packing Lists - ML package
- Payslips - ML package
- Passports - ML package
- Purchase Orders - ML package
- Receipts - ML Package
- Remittance Advices - ML package
- UB04 - ML package
- Utility Bills - ML package
- Vehicle Titles - ML package
- W2 - ML package
- W9 - ML package
- Public endpoints
- Supported languages
- Insights dashboards
- Data and security
- Licensing and Charging Logic
- How to
Publish
- Create a project version: freeze the current models state into a project version.
- Deploy project version: make the models accessible from workflows.
- Automate your process: consume the product version in an automation and open Studio Desktop or integrate using APIs.
- Export dataset so you can use it in a different tenant or organization, or just save it as a backup.
A project version is a snapshot of the current models state. Since the Classifier and Extractor models are trained continuously as you upload data or interact with the model, you can use the Project version feature to freeze the current state of the models if you are satisfied with the performance. Once a project version is created, you can start using your models in a workflow.
Once a project version is created, model training is automatically kicked off. Both Classifier and Extractor selected during process version creation are trained on all uploaded data. Depending on the model and the size of the dataset, this can take from a few minutes to several hours.
- Training: Models in the project are being trained. This is a transitory state.
- Trained: Models in the project are trained.
- Undeployed: Models trainining is complete, but the models are in idle state. Models are not consuming any resources and the project version cannot be referenced from, or used in workflows. Undeployed project versions are not available in Studio activities.
- Deployed: Models training is complete, and the are running. Models are consuming hardware resources and the project version can be referenced from and used in workflows.
To deploy a project version, click on the toggle from the Deployed column.
Once a project version is deployed, you can use the models in workflows.
- Extract Document Data and Classify Document activities from the DocumentUnderstanding.Activities package.
- Document Understanding Project Classifier and Document Understanding Project Extractor from the IntelligentOCR.Activities package.
If you are using Document UnderstandingTM Cloud APIs, you can also use the project in your API automation. You can do this easily be selecting Integrate via API.
If you select Integrate via API, a new window with the code is displayed. Here, you have the option to select your preferred programming language and paste this code into your preferred editor. However, please remember to modify the specified variables before consuming the deployed project via REST APIs.
- Import them into another modern project from a different tenant or organization.
- Import them into a classic
project. For more information on how to import datasets into a classic project,
check the Document Understanding User Guide for
classic projects.
Note: Datasets exported from modern projects are compatible with classic projects only when training on model version 23.4.0 or newer.
For more information on how to export datasets and migrate your modern projects, check the Migrating modern projects page.
