Inspiration ‼️

Our inspiration for CartWatch came from one of our members, who was very surprised to see how much money he spent this summer on impulse online shopping. Upon further research, we found out just how much of a problem savings was for most Americans. While this problem stems from the high cost of living, we feel that small savings can build into large savings over time.

What it does 🤔

There main functionality of CartWatch is a google chrome extension that detects when user's are about to make a purchase. User financial health data is retrieved and the customers will be alerted if they can't afford to purchase an item. Aditionally, CartWatch offers a web and mobile app dashboard to visualize spending history.

How we built it 🛠️

We started by splitting the challenge into two parts, detecting the purchase, and then providing an input. Detecting the purchase relied upon parsing the webpage's html data for certain keywords and contexts. Once at a certain score, the DOM was sent to gemini api for further confirmation that a purchase was going to be made. The backend part of the project relied upon using the nessie API to generate transaction and account history for mock users, then populating a data base with this information. To sync data, a cron job script is run every night. Part of the script uses a statistical model to determine the financial health of a customer, which is stored in the database. The extension interacts with this data to provide feedback to the user. Once that functionality was implemented, we developed a mobile and web dashboard to display information.

Challenges we ran into 🧱

We had little experience with full stack development. This project required a lot of learning on the spot.

Accomplishments that we're proud of 💯

We are proud at the UI we've developed, the design feels really sleek and professional.

What we learned 📖

We learned problem solving, creative thinking, and of course technical skills.

What's next for CartWatch 🔮

Incorporation with real banking services using PLAID's API's. Migrating our database to MongoDB. Creating our own custom trained AI model for financial health analysis. Cron Jobs on redis, forward facing API. DEPLOYMENT!

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