Testing your learning instances before moving them to production ensures that such learning instances meet your expectations in terms of the performance, quality, and reliability of the extracted data.

As a Document Automation developer, you can use the Test mode option in learning instances to try different settings, such as using different OCR providers, generative AI providers, different generative AI prompts, and turning validation feedback on or off.

Benefits of testing your learning instances

  • Data accuracy and reliability: Ensures accurate and reliable data extraction from different document types. It helps identify and correct errors, preventing inaccurate data from affecting downstream systems. Robust testing maintains data integrity across different formats and layouts, verifies correct field mappings, and ensures OCR works well for different document types. This is important to avoid costly errors and disruptions in business operations.
  • Handle document variations: Ensure that the system can extract data from documents with different qualities, formats, and layouts.
  • Performance optimization: Check processing speed, find potential bottlenecks in the workflow, and ensure resources are optimally utilized.
  • Generative AI prompt validation: Ensures that the generative AI prompts work as expected.
  • Confidence scores: Verifies the accuracy of the confidence scoring system and ensures that the low-confidence data is flagged appropriately for human validation.
  • Organization requirements: Ensure that the system meets the specific business needs and validates the return on investment (ROI) by demonstrating the system's ability to automate data extraction and improve efficiency.

End-to-end workflow of testing learning instances

The following image shows the workflow of how the learning instances are tested in one environment and moved to another before being used by users:

End-to-end workflow of testing learning instances across different environments before deploying it for use
Stage 1
  1. Create or edit an existing learning instance. See Create a learning instance in Document Automation.
  2. Enable test mode for the learning instance. See Enable test mode for learning instances.
  3. Configure the learning instance and save the changes. See Create a learning instance in Document Automation.

    A new version is created whenever you make changes to the learning instance configuration.

  4. Process sample documents to validate data extraction results. See Process documents in test mode.
  5. Validate the processed document to check if the data is extracted as expected. See Validate documents in test mode.
  6. Compare the data extracted from different versions of the learning instance to find any configuration changes that might improve data extraction. See Compare versions of a learning instance.
  7. Repeat step 3 through step 6 until you get the desired results.
  8. After you get the desired results, export the learning instance from the development (Dev) environment and import it into the UAT environment. See Export and import learning instances.
Stage 2
Repeat the steps provided in Stage 1 to move the learning instance from one environment to the next.
Stage 3
Synchronize (sync) the learning instance across all the environments.