Business Implications
Steps Performed
Implemented an S3-triggered Lambda that calls Textract, normalizes output, writes items to DynamoDB, and emails stakeholders via SES; included IAM hardening and end-to-end testing.
1.
Configure SES Identities & Alerts
Verified sender/recipient identities in Amazon SES, set sandbox-mode emails, and defined notification content (vendor, date, total, S3 link). Established a reliable channel for post-processing confirmations and escalation.
2.
Provision Storage & Database
Created an S3 bucket (with incoming/ folder) for uploads and archiving. Defined a DynamoDB table Receipts with receipt_id (PK) and date (SK) to enable time-based queries and itemized storage.
3.
Create IAM Role & Lambda
Built ReceiptProcessingLambdaRole with least-privilege access to S3, Textract, DynamoDB, SES, and logging. Implemented ReceiptProcessor (Python) to call Textract AnalyzeExpense, parse summary fields and line items, persist to DynamoDB, and send SES emails.
4.
Wire S3 Event Notifications
Added S3 ObjectCreated notifications (optionally restricted to incoming/ and image/PDF suffixes) to trigger the Lambda. Increased Lambda timeout and set environment variables for table name and SES addresses.
5.
Test, Validate, And Improve
Uploaded sample receipts to S3, monitored in CloudWatch Logs, verified DynamoDB items and SES emails. Documented clean-up and extensions: categories, monthly summaries, SNS error alerts, image compression, and status tracking.
AWS Services Used
Amazon S3
Amazon Textract
Amazon DynamoDB
Amazon SES
AWS Lambda
AWS IAM
Python
Boto3
AWS CLI
CloudWatch Logs
Technical Tools Used
Serverless Workflow Design
OCR & Structured Extraction
Event-Driven Integration
NoSQL Data Modeling
Skills Demonstrated
Automated Receipt Processing System - Amazon Textract
Serverless OCR, Storage, Alerts With AWS
Built a serverless pipeline that ingests receipt images/PDFs to S3, extracts structured data via Amazon Textract, stores records in DynamoDB, and sends email alerts with Amazon SES. AWS Lambda orchestrates real-time processing for scalable, low-ops record-keeping and audit readiness.
