Building a Document Processing Pipeline with AWS Services

The traditional way to analyze documents and extract insights was through manual processing. It used to be a time-consuming process with a high probability of errors. Using AI, we can automate this process, making it much faster and more accurate. To help us do that, Amazon provides AI tools such as Textract and Comprehend. Textract can help us extract data from images and documents. The extracted data is in the form of text. This textual data can then be fed to Comprehend, an NLP tool that analyzes textual data. In response, we’ll get the necessary insights.

In this Cloud Lab, you’ll learn to automate document processing using multiple Amazon services.

To do that, you’ll first create an S3 bucket where the input and output data will be stored. After that, you’ll create an IAM role to provide necessary permissions to other AWS services. You’ll then create a Lambda function to execute a piece of code that will feed the data stored in the bucket to Textract to convert it to text. This text will then be processed using Comprehend, and the output of Comprehend will be stored in the output folder of this bucket. Finally, you’ll integrate an email service in the pipeline using Amazon SES.

After completing this Cloud Lab, you’ll have a pipeline for extracting and processing text from documents using AWS services. Completing these tasks will equip you with practical knowledge of how to utilize these AWS services to automate document processing tasks.