Dealify

How we used AI this weekend
Slider containing the best prices
Homepage, where the user can either search for an item or scan it

Inspiration

Inflation has become a widely discussed topic, particularly when it comes to the rising cost of groceries. We wanted to tackle this challenge and help those who struggle to find affordable products in their area. The process of comparing prices across multiple websites for every item can be time-consuming and frustrating, often leading to only minor savings. Our goal is to simplify this process and make it easier for people to access the best deals without the hassle.

What it does

Dealify is designed to make this process seamless and hassle-free. Simply enter your grocery list, and Dealify will automatically scan prices from various stores in your area, providing a clear comparison of total costs at different locations. This allows you to easily choose the most affordable option without the tedious manual searching. Additionally, Dealify lets you scan any price tag in-store and instantly compare it with other nearby options, ensuring that you always get the best deal and never overpay for your groceries.

How we built it

Dealify is currently a mobile app developed in Swift for iOS, supported by a robust TypeScript backend that manages all major communications between the app and its data. In addition, Dealify integrates a Flask backend specialized in data analysis and image recognition, complementing the main backend's functionality.

To ensure accurate and up-to-date pricing, Dealify maintains a PostgreSQL database that stores all items and their corresponding prices for comparison. This database is continuously updated through a web scraping tool that retrieves pricing data from major retailers. Both backends, along with the database, are efficiently deployed on Render, ensuring smooth operation and scalability.

Challenges we ran into

We encountered multiple challenges throughout the development process, starting with the fact that none of us had prior experience with Swift before embarking on this project. Additionally, integrating a diverse tech stack proved to be complex, as merging all components into a seamless system required careful coordination. Another significant hurdle was the scraping tool, as each website we collected data from had a unique structure, making it difficult to implement a one-size-fits-all solution.

Accomplishments that we're proud of

We are incredibly proud to present a fully functional app with robust features. Despite the new and complex challenges we faced along the way, we remained dedicated and worked tirelessly to develop a product that meets our vision. Our perseverance and commitment have resulted in an app we can confidently stand behind.

What we learned

Throughout this project, we gained valuable experience in setting up a database from scratch, developing a full-stack mobile application, and efficiently scraping large amounts of data. Additionally, we learned how to implement effective search functionality, allowing users to find relevant results even when their queries are not perfectly structured.

What's next for Dealify

With ongoing app usage and the continuous collection of diverse datasets, we aim to develop a dashboard that analyzes price variations across different brands. This will provide users with valuable insights into pricing trends, helping them make informed decisions and shop at stores that consistently offer the best prices.