Budget Helper AI

Inspiration

Personal finance is a crucial part of everyday life because it is crucial for meeting your personal finance goals – having enough for food and rent, paying off your student loans, saving up enough to go on vacation abroad, or saving for your child's own education. Not understanding how to manage finances has led many Americans to accumulate tremendous amounts of debt over the last few decades, which makes learning personal finance more important than ever! Our aim is to give people the tools they need to manage their money and get financial advice using artificial intelligence. Anybody can use BHAI today, along with its budget tracker and AI chatbot which helps users make sound financial decisions.

What it does

Budget Helper AI (BHAI) is a cutting-edge budgeting app that not only helps users monitor their cash inflows and outflows but also provides personalized spending advice through an AI chatbot. What sets it apart is its unique feature of scraping real-time data from Walmart's official website, enabling users to discover more budget-friendly alternatives for various items without compromising quality. Transform your financial management experience with BHAI, where intelligent guidance meets practical budgeting solutions.

How we built it

The project started as a simple app that can help college students' track their daily expenses. We initially tried to build an app like this because, as college students, we have experienced how hard it can be to manage your money when you don't have very much of it. After brainstorming ideas on what else the app could do to help users make sound financial decisions, we changed our approach to a more general one. The idea then transformed into a universal fintech tool that can be used by anybody.

Challenges we ran into

The front end of this project was programmed in JavaScript using React.JS whilst the back end was created using Python, Flask, and Firebase. It was difficult connecting the front end and back end because sending search queries from the front-end to the back-end for parsing and output involved a complex process. First, the front end has to convert the search query data to a JSON format and send it to the back end. Then, the back end decodes the JSON data and parses it using Python, Firebase, and real-time data. After parsing, it reconverts the parsed data to a JSON format and sends it to the front end, where the data is decoded and shown to the end user. Figuring out how to carry out this complex process took up much time, but it led to great results in the end.

Accomplishments that we're proud of

The app's unique integration with Walmart's real-time data has enabled users to discover cost-effective alternatives, leading to substantial budgetary improvements.

What we learned

The app has illuminated the significance of personalized financial guidance, demonstrating that users greatly benefit from AI-driven advice tailored to their unique spending patterns. The integration of real-time data from Walmart has highlighted the importance of convenience and budget-friendly options, shaping our understanding of user priorities in the realm of personal finance. Continuous learning from user interactions has allowed us to refine and enhance the app, ensuring it remains a dynamic and indispensable tool for fostering financial well-being.

What's next for Budget Helper AI

Broaden the range of real-time data sources, ensuring users have access to the most relevant and up-to-date information for smarter decision-making
Add an account system, so that users can save their budget plans and recommendations
Support additional expenses, such as transportation, tuition fees, etc.