Building an Invoice Processing App with Python and AWS Textract

Pushkar Nandgaonkar
May 5
3 min read

In today’s fast-paced digital world, businesses, startups, and freelancers are constantly buried under piles of paperwork—especially invoices, receipts, and transaction records. Manual processing not only consumes a lot of time but also increases the likelihood of errors, especially when dealing with bulk documents. Now, imagine an intelligent system where you just upload a scanned invoice, and in seconds, you receive neatly structured and searchable data extracted from that file. Sounds like something out of science fiction? Fortunately, it’s very real—thanks to AWS Textract and the versatility of Python.

For students eager to build a project that’s both impactful and resume-worthy, this blog offers an exciting opportunity to dive into AI-powered document processing. By combining cloud computing and artificial intelligence, you’ll learn how to automate a real-world task that every modern business can benefit from. Whether you're preparing for your capstone project, a coding competition, or simply looking to level up your skills, this is a powerful project to take on.

Manual Invoice Processing is Outdated

Manual data entry from invoices or receipts is tedious, error-prone, and a waste of valuable time. Think about it:

Every detail must be typed out manually.
Typos can lead to accounting errors.
Processing in bulk? It's a nightmare.

Whether it’s for a class project, a freelance gig, or an internship assignment, building a smarter solution to this problem will not only enhance your technical portfolio but also your understanding of applied machine learning.

Solution: Automating Invoice Extraction Using AWS Textract

AWS Textract is a powerful AI service that automatically extracts text, form data, and tables from scanned documents. By integrating it with a Python-based app, you can create an automated pipeline to process invoice images in seconds.

Here’s a simplified step-by-step breakdown to guide your own version of the project:

Step 1: Set Up AWS Textract

Sign in to AWS and enable Textract.
Create an IAM user with permissions to access Textract.
Generate access keys to use in your Python script.

Step 2: Prepare Your Environment

Install the required libraries: boto3, Pillow, and pdf2image if working with PDFs.

pip install boto3 Pillow pdf2image

Step 3: Upload and Process the Document

Write a Python script to upload an image or PDF to Textract.
Call the analyze_document API to extract data.

Step 4: Extract Key Information

Parse the response to extract fields such as:
- Invoice Number
- Date
- Vendor Name
- Total Amount
- Line Item Details

Step 5: Display or Save the Results

Present the results in a tabular format using a Python GUI (like Tkinter) or save the output in a downloadable format like CSV or JSON.

Why This Project Matters

This kind of project does more than just showcase your Python skills. It introduces you to real-world applications of AI and cloud computing. Whether you’re aiming for a role in data science, software development, or AI engineering, this experience stands out.

Plus, it has immediate practical use—small businesses, freelancers, and even finance teams need this kind of solution.

Need Help Building Your Project?

At CodersArts, we specialize in helping students build real-world, AI-powered solutions for assignments and academic projects. Whether you’re stuck on AWS setup, parsing data, or building the interface, we’re here to help you succeed.

You can also check out the project demo in the following video: