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Home Page
Inspiration
Help students with student debt
What it does
Track, save, and invest in a young adults career powered by AI to allow automatic categorization. After logging in the user can set saving goals, get an overview about his earnings and expenses. The transactions of the users get automatically classified using a NLP model. The user receives information through text messages and can interact with the server by sending texts.
How we built it
Our modern Frontend was created with React, our Backend consists of a Node.js storing the data in our MongoDB. Additionally we added a Python Flask Microservice which is responsible for classifying the transactions based on a finetuned NLP model. Twilio is integrated to inform the user once they get closer to their saving goals and keep them engaged. Additionally, users can save transaction with a short text message which can be used for expenses payed with cash. The frontend provides a contact page, which sends an email to our team.
Challenges we ran into
Adding data the the pie charts, deploying a large NLP model for free, saving a huggingface model with tensorflow
Accomplishments that we're proud of
NLP classifier in production, nicely layouted website aswell as a modular backend which accepts requests from different types of clients.
What we learned
Quality over quantity, keep going, you can make it!
What's next for SaveExp
Add features, e.g. automatically get transactions data from backend account. More filter and customization options in the frontend. App
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