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Capstone Project Idea: Build an AI-Based Document Processing System using AWS Textract


If you're on the lookout for a powerful, real-world capstone project that blends artificial intelligence with practical applications, here's a brilliant idea: Build an AI-Based Document Processing System using AWS Textract. Not only is it an impressive project to showcase on your resume, but it also addresses a common pain point in many industries, making it a valuable learning experience.


Let’s break it down into what the project involves, the tools you'll use, and how you can successfully execute it.


Why Document Processing Is a Valuable Project Topic

From universities to businesses, handling structured and semi-structured documents—like ID cards, invoices, and application forms—is a daily task. Manual entry is not only time-consuming but also prone to errors. That’s where AI-powered tools like AWS Textract come in. They can extract, structure, and export data automatically and accurately.


By creating an AI-based document processing system, you’ll gain hands-on experience in:

  • Working with OCR (Optical Character Recognition)

  • Handling real-world document types

  • Using cloud-based AI services

  • Developing scalable data workflows

This is the kind of project that showcases both your technical and problem-solving skills.


Project Scope

Your AI-based document processing system will:

  • Accept scanned documents or images (e.g., ID cards, receipts, application forms)

  • Use AWS Textract to extract fields like Name, Address, Document Number, and Date of Birth

  • Display extracted data in a user-friendly interface

  • Allow data export to CSV, Excel, or JSON formats

  • Support multiple document types with varying layouts

  • Ensure accuracy by displaying confidence scores from AWS Textract


You can also enhance the project with features like:

  • Image pre-processing using OpenCV

  • Integration with cloud storage (e.g., S3)

  • REST API endpoints for document upload and data retrieval

  • User authentication to secure sensitive data


Suggested Tech Stack

Here’s a beginner-friendly yet robust stack for building this project:

  • Frontend: HTML, CSS, JavaScript (or React.js for a more modern approach)

  • Backend: Python (Flask or FastAPI)

  • AI Service: AWS Textract

  • Storage: AWS S3 for storing document images

  • Database: SQLite or PostgreSQL (depending on scale)

  • Export Tools: Pandas (for Excel/CSV output), JSON module


Implementation Steps

  1. Document Upload Interface

    • Create a simple web form or drag-and-drop feature to upload images or PDFs.

  2. Integrate AWS Textract

    • Use the AWS SDK (boto3) in Python to send images to Textract and receive parsed data.

  3. Data Processing & Display

    • Organize the extracted fields and display them clearly, with confidence scores.

  4. Data Export Options

    • Let users download the data in Excel or JSON format for further use.

  5. Optional Enhancements

    • Add a login system

    • Include an admin dashboard

    • Build API routes for integration with other systems


Real-Life Demonstration

Check out a working demo of this concept in action. AWS Textract processes different ID documents in seconds and exports the results accurately, no matter the format:




Get Support When You Need It 

Feeling inspired but unsure where to start? Whether you're struggling to set up AWS, define your project structure, or debug your code, CodersArts offers the mentorship and technical support you need. From idea validation to complete project execution, our experts help you every step of the way—so you can focus on learning and building.

Start strong, build confidently, and finish with a capstone project you’re proud of.


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




Need personalized guidance on this project or a similar one? Reach out to CodersArts today and get expert support tailored to your needs.




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