Eco-Budgeter

This project summary captures the journey of creating Eco-Budgeter, a financial tool designed to align personal spending with environmental values.

Inspiration The inspiration for Eco-Budgeter came from the realization that while many people want to live more sustainably, they often lack clear visibility into how their daily purchases affect the planet. We wanted to bridge the gap between financial literacy and environmental impact, proving that being "green" can also keep your wallet "in the black."

What it does Eco-Budgeter is an AI-powered financial management platform that:

Analyzes Receipts: Uses Gemini AI to scan receipt images, extracting itemized data, quantities, and prices automatically.

Eco-Scoring: Audits purchases to provide an "Eco-Score" based on factors like supporting local businesses and minimizing plastic use.

Financial Dashboard: Provides a high-level view of monthly income, fixed expenses, and progress toward saving goals.

Visual Analytics: Generates spending reports and pie charts to visualize habits over time.

AI Financial Advisor: Offers personalized tips to hit savings goals while suggesting more sustainable alternatives.

How we built it Frontend: Built with Next.js and Tailwind CSS for a responsive, tabbed user interface.

Backend & Database: Leveraged Supabase for user authentication, real-time data storage, and budget profile management.

AI Engine: Integrated Gemini 1.5 Flash to handle complex receipt analysis and generate financial insights.

Data Visualization: Implemented Recharts to transform raw expense data into interactive spending breakdowns.

Challenges we ran into Granular Data Extraction: Teaching the AI to distinguish between the total price and individual item quantities required refined prompt engineering and schema validation.

State Management: Handling complex "Advanced Manual Entry" forms where users can modify individual items within an array while maintaining UI reactivity was a significant logic hurdle.

Financial Logic: Calculating a dynamic "Remaining Budget" while accounting for income, fixed costs, and variable receipt spending required careful database architecture.

Accomplishments that we're proud of Successful AI Integration: Building a system that can accurately turn a messy receipt photo into a structured, editable database entry.

Full CRUD Functionality: Developing a robust system where users can not only scan receipts but manually add, edit, and delete granular purchase data.

Budgeting Suite: Successfully implementing a financial advisor that understands both the user’s bank account and their environmental footprint.

What we learned Controlled Components in React: We learned the importance of sanitizing database inputs to avoid "null value" warnings in UI components.

Data Aggregation: We mastered complex reduce functions to group disparate receipt items into clean, readable summaries.

The Power of AI in FinTech: We discovered how AI can transform passive expense tracking into active, insightful financial coaching.

What's next for Eco-Budgeter Gamification: Introducing badges and social leaderboards for users with the highest Eco-Scores.

Bank Integration: Moving beyond manual scans by integrating directly with bank APIs for real-time transaction auditing.

Product Alternatives: Expanding the AI advisor to recommend specific, lower-carbon-footprint product alternatives for items found on receipts.

Built With

• gemini-api
• next.js
• node.js
• supabase