🧾 AWS Receipt Processing System using Textract

This project is a serverless application that automatically processes receipt images uploaded to an Amazon S3 bucket. It uses Amazon Textract to extract structured data, stores the result in DynamoDB, and sends email notifications using Amazon SES.

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📌 Use Case

A user uploads a receipt image to S3, and the system extracts data like date, total amount, vendor name, etc., then stores it and notifies the user.

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🛠️ Architecture Overview

Components:

1. Amazon S3 – Stores uploaded receipt images.
2. AWS Lambda – Serverless logic for orchestrating the workflow.
3. Amazon Textract – Extracts text and data from the receipts.
4. Amazon DynamoDB – Stores structured receipt data.
5. Amazon SES – Sends email notifications after processing.

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🔁 Workflow

1. 🧑‍💼 User uploads the receipt image to an S3 bucket.
2. ⚡ S3 triggers a Lambda function upon new upload.
3. 🔍 Lambda invokes Textract to extract text/data from the image.
4. 📄 Textract returns structured JSON data back to the Lambda.
5. 🗃️ Lambda stores the extracted data in a DynamoDB table.
6. 📧 Lambda uses SES to send an email notification to the user.

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⚙️ Setup Instructions

1. Create the following AWS resources:

   • An S3 bucket for uploads
   • A DynamoDB table (e.g., ReceiptsTable)
   • A verified email identity in Amazon SES
   • A Lambda function with appropriate IAM roles

2. Configure environment variables for the Lambda:

   TABLE_NAME= name_of_the_table
   EMAIL_FROM=your_verified_email@example.com
   EMAIL_TO=user_email@example.com

3. Deploy the Lambda function and set up an S3 trigger.

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✅ Example Output

Once a receipt is uploaded:

• The extracted fields (e.g., Total Amount, Vendor, Date) are stored in DynamoDB.
• An email is sent to the user with a summary.

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📝 Notes

• Make sure Amazon SES is in production mode or email identities are verified.
• Textract works best with clear, high-resolution images.
• All resources should be deployed in the same region (e.g., us-east-1).