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Document Automation

  • Updated: 2022/09/22
    • Automation 360 v.x
    • IQ Bot
    • Process flow
    • Digitize

Document Automation

Document Automation is the new Cloud-native intelligent document processing solution that business users can set up to automatically read and process documents quickly using pretrained models and validation feedback.

Document Automation is fully integrated into Automation 360: Document Automation is installed as part of the Control Room, RPA bots are used to extract semi-structured data to automate document-centric business processes, and Automation Anywhere Robotic Interface manages the end-to-end extraction process and validation tasks.

Document Automation combines with AARI and RPA bots to automate document processing

The Document Automation workflow enables users to scale their document processing operation. Users create learning instances that use Automation Anywhere or Google Document AI pre-trained models to process invoices, utility bills, and receipts. Once a learning instance is running in production, it automatically improves extraction accuracy based on feedback from manual validation.

To compare Document Automation features side by side with Automation 360 IQ Bot, see Intelligent Document Processing solutions feature comparison matrix.

Set up the Document Automation environment

Document Automation is installed simultaneously with the Control Room and shares the Control Room database. There are no additional installation tasks for Control Room Cloud customers.

To get started using Document Automation, you must first configure users, roles, and devices, and connect the Control Room with Automation Anywhere Robotic Interface:

Set up your Document Automation environment

Note: To install Document Automation in an On-Premises server, note the following:
  • The Control Room stores Document Automation output data.
  • You must install the Control Room in a configuration that points to the location where Document Automation data is stored. Ensure there is sufficient storage space.
  • The minimum necessary storage space depends on the processing volume, document size, and use case. As a guide: an environment that processes 100,000 pages per month, with a 30-day data lifespan, requires 500 GB of storage space.

Using Document Automation

The following is an overview of the end-to-end process to create, configure, and publish a learning instance in Document Automation:

Step 1: Create a learning instance
Log in to the Control Room as the learning instance creator user, and create a learning instance to extract values from documents.
Step 2: Process documents
Upload documents to the learning instance to test the model, fix validation errors, and verify the extracted data.
Step 3: Build a bot to upload documents to Document Automation
Build a bot that uploads documents from a source folder to Document Automation.
Step 4: Publish the learning instance
Check-in the learning instance assets (process, form, and bots) to the public repository. Then, deploy the process and bots to unattended Bot Runner devices to begin processing documents in real time.
After the process is deployed, incoming documents are processed, and Document Automation either extracts data from the documents or sends the documents for validation.
Step 5: Validate the uploaded documents
Log in as the Validator user, open the validation queue, and use the Validator to fix errors.
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