Home page where user can check all his/her transactions and their money spending.
This is Spending section where user can add their spending details and their transactions.
This Overview section where user can analyse how his/her spending amount on different usecases, in that graph it shows the user spendings.
This is Saving simulator , it simulates the user savings details.
This Goals page where user can create goals for their upcoming/future spendings.They can plan themselves how to spend this money for future.
This is Finaura copilot Ai , in which user can ask and clarify doubts on their transcations and money spendings and queries regarding spends

Inspiration.

Many students and young professionals struggle to manage limited income, daily expenses, and savings goals. They often don't know whether their current spending will leave them with enough money at the end of the month. I created Finaura to make personal finance easier to understand through clear projections, spending insights, and practical what-if scenarios.

What it does.

Finaura is an AI-powered personal finance assistant that helps users understand their spending and plan their finances. It supports transaction tracking, CSV imports, expense category analysis, month-end balance projections, savings goals, and hypothetical spending-reduction scenarios. It also provides controlled AI-assisted explanations using fictional sample data, while financial calculations are handled by deterministic logic.

How we built it

Finaura was built as a full-stack web application using React, Vite, and Tailwind CSS for the frontend, with Node.js and Express for the backend. Financial calculations and transaction processing are implemented in JavaScript. The application includes CSV parsing, forecast calculations, savings-goal planning, what-if scenarios, and automated tests. AI-assisted explanations use a restricted set of fictional sample scenarios to help maintain a clear privacy boundary.

Challenges we ran into

One of the main challenges was ensuring that financial projections were consistent and did not double-count past transactions. I also needed to validate CSV imports, handle missing financial information safely, and prevent AI-generated explanations from inventing financial figures. Automated tests helped verify the calculations, error handling, and privacy boundaries.

Accomplishments that we're proud of

We're proud of building Finaura as a working full-stack personal finance assistant rather than just a static dashboard. We implemented financial projections, CSV transaction importing, spending analysis, savings-goal planning, and what-if simulations. We also built automated tests to verify our financial calculations, input validation, and privacy safeguards. Our biggest accomplishment is combining practical financial tools with responsible AI-assisted explanations, while keeping calculations deterministic and avoiding unsupported financial claims.

What we learned

Building Finaura helped me understand how to turn a real-world problem into a working application, organize frontend and backend components, test financial logic, and integrate AI responsibly. I learned that financial applications need reliable calculations, clear explanations, and privacy safeguards rather than relying on AI alone.