Published Paper Details:

The main aim of this project is to develop and deploy an Expense Tracker application that enhances the management of finances through the utilization of advanced technologies. The application incorporates Optical Character Recognition to scan and extract information from invoices and receipts, along with a Large Language Model that classifies expenses into pre-defined categories. Using Flask for the frontend and Python for the backend, the project promises a smooth and friendly user interface. The OCR component employs sophisticated text recognition techniques to pull out transaction information from receipts, while the LLM categorizes transactions into typical expense categories such as food, utilities, and entertainment. Additionally, the app shows these categorized expenditures through interactive graphs and detailed transaction lists on the dashboard, offering users insightful information about their expenditures. This project showcases the successful integration of OCR and LLM technologies in actual applications, underlining the potential for automation of everyday financial work. The system seeks to enhance financial literacy and allow users to make knowledgeable choices, hence encouraging efficiency as well as access in managing expenses.