Landing Screen
Interests Questionnaire
Home Page
Liked Books Page
Book Information Page

Flippr - A Personalized Book Recommendation App

Inspiration

In today’s fast-paced educational system, students, educators, and casual readers alike face a common problem: finding the right book that fits their interests and reading level. With the sheer volume of books available, it’s often difficult to choose one that matches both personal preferences and educational needs. We realized that decision paralysis is a major hurdle in accessing books that can benefit learning and personal growth. This challenge inspired us to create Flippr, an app that leverages AI to recommend books based on the user’s specific interests and preferences, helping readers find their next book faster and more effectively.

What it does

Flippr is an intuitive mobile app that personalizes book recommendations based on a user’s preferences. After filling out a short questionnaire, users can swipe through AI-curated book suggestions, liking or passing on books based on their interests. The app tracks user preferences and tailors future recommendations accordingly. Over time, the AI improves its suggestions, creating a seamless book discovery process. Users can also save books they like for later reading, helping them build a personal reading list.

How we built it

We built Flippr using:

React Native for developing a cross-platform mobile app.
Expo for smooth app development and testing.
Node.js & Express for the backend, managing API requests, user data, and handling the book recommendation engine.
MongoDB for storing user preferences, liked books, and book data.
OpenLibrary API to source book metadata like titles, authors, and cover images.
GPT-4o that analyze user preferences and deliver personalized book recommendations.
Cerebras-AI a faster way of producing summaries and information on books.

Challenges we ran into

Building Flippr came with its fair share of challenges. One of the biggest obstacles was creating an AI-driven recommendation system that accurately captured user preferences and adapted over time. Ensuring a seamless user experience, particularly with the swipe-based book selection interface, required careful design and debugging. Managing real-time database updates while preserving a smooth app experience was another technical challenge, especially as user interactions needed to be processed quickly and without lag. MongoDB was new to all of us and we had to learn how to connect, add items, and fetch items from the database. It was the toughest challenge as most of the complexity in the backend comes from the backend work.

Accomplishments that we're proud of

We’re incredibly proud of the personalized recommendation engine we built, which tailors book suggestions to each user’s preferences. Additionally, we were able to integrate a swipe-based interface that’s both engaging and easy to use. Our smooth backend integration ensures that users’ book preferences and saved lists are updated in real time, providing a responsive and reliable experience. Above all, we’re proud that Flippr addresses a real-world problem in education and personal reading, offering a tool that can enhance the learning process for countless users. This was our first time building a mobile and were able to do so by building a clean UI and persevering with errors through the backend.

What we learned

Throughout the development process, we gained valuable experience in building mobile apps that are both user-friendly and data-driven. We improved our understanding of integrating APIs, handling asynchronous data fetching, and building scalable backend systems. We also learned how to incorporate AI models into an app to make personalized recommendations, which will be useful for future projects. Building Flippr helped us refine our skills in frontend development, especially in managing state and ensuring cross-platform compatibility with React Native. We learned how backends operate and how MongoDB functions as a database.

What's next for Flippr

Looking ahead, we plan to further enhance Flippr by integrating more advanced AI algorithms to make book recommendations even more accurate and tailored. We want to add community-driven features, allowing users to see what others are reading and recommending. We also aim to include more educational features like book summaries, learning resources tied to recommended books, and integrating book reviews. Expanding the database to include a wider variety of books will further enrich the user experience. Additionally, we hope to bring Flippr to web browsers, expanding accessibility beyond mobile platforms.