Automate Labeling for Intelligent Document Processing with Cognizant and Amazon SageMaker Ground Truth

This article describes a solution by Cognizant to automate labeling of documents for intelligent document processing (IDP) using AWS services like Amazon SageMaker Ground Truth, AWS Lambda, and AWS Step Functions.

Specifically, the article covers:

• The challenges of manual labeling for IDP, such as costly and time-consuming efforts, the need for domain expertise, integrating training data with inference pipelines, and handling complex information extraction.
• An overview of Cognizant's IDP solution, which involves uploading documents to Amazon S3, triggering a job management workflow in AWS Step Functions, creating a labeling job in Amazon SageMaker Ground Truth with a custom UI for SMEs, and post-processing the labeled data into various formats for model training.
• Key components like the job management workflow, the Amazon SageMaker Ground Truth custom UI, and the post-processing stage.
• Considerations and impact, including improved model accuracy and F1 scores by using the solution for transfer learning and fine-tuning foundation models.
• Conclusion highlighting the benefits of automated document labeling at scale for IDP and the role of this solution in handling complex data and aligning generative AI models.