Note Ninjas

Early version of the application.
Early version of the application, generating notes for Computer Networks.
version with small flashcards
final version at start
final version with generated study guide, large flashcards
NoteNinjas logo
System architecture flow chart

Personal Knowledge Management Track

Inspiration

This project was born out of frustration with study tools like Quizlet becoming increasingly paywalled and less user-friendly. We often found ourselves buried in disorganized notes, unsure of what was important, and spending too much time making flashcards manually. We wanted a faster, smarter way to turn notes into study materials—one that used AI to do the hard work and helped students like us focus on learning, not formatting.

What it does

NoteNinjas takes in notes—either typed directly or uploaded as a text file—and uses AI to generate a study guide automatically. This guide includes a list of key terms with definitions, and quiz-style question and answer flashcards. It allows students to quickly review and test themselves without manually creating flashcards or filtering through large blocks of text.

How we built it

Frontend: Built with React and JavaScript, deployed using AWS Amplify for easy hosting and scalability.
Backend: A Python-based AWS Lambda function processes the input and communicates with the AI.
AI Integration: The Lambda backend calls AWS Bedrock, which uses foundational models to extract key information and generate study materials.
Communication: AWS API Gateway connects the frontend to the backend, and IAM roles ensure secure, permission-based access across services.
Accessibility: Text-to-speech support using Amazon Polly for auditory learning

Challenges we ran into

Getting IAM permissions right so Lambda could call Bedrock securely.
Formatting prompts and parsing Bedrock’s responses into clean, structured data.
Handling both text input and file uploads on the frontend while maintaining a smooth user experience.
Debugging API Gateway, Lambda, and Amplify so that they all communicated properly with each other.

Accomplishments that we're proud of

Built a functional AI-powered tool that generates study material from user notes, saving time and effort.
Integrated multiple AWS services into a cohesive, secure system.
Designed a clean and intuitive UI that simplifies the studying process.
Solved a real-world problem that many students face with note overload and inefficient review methods.

What we learned

How to deploy and scale serverless functions with AWS Lambda
How to use AWS Bedrock for prompt-based AI tasks
Best practices for connecting cloud services securely with IAM and API Gateway
How to build and deploy a full-stack web app using modern web frameworks and cloud tools

What's next for NoteNinjas

Support for more file types like PDF and Word documents
Export to Anki, Quizlet, or CSV formats
Add user accounts and authentication so people can save and revisit study guides
Explore subject-specific AI models to improve accuracy for STEM or humanities topics