Project · AI Fintech
SpendDecode
AI-powered personal finance and spending intelligence.
A personal finance platform that helps people understand their transactions, analyse spending habits, find saving opportunities, and make better purchasing decisions — with an AI layer that explains the numbers instead of just charting them.
What problem does SpendDecode solve?
Bank and UPI statements list transactions but don't explain them. SpendDecode reads an uploaded statement, organises the transactions and explains spending patterns in plain language, so people can budget, save and make purchase decisions with their own data in front of them.
Key features
- Expense and spending analytics
- AI-powered financial insights
- Transaction understanding
- Money-saving recommendations
- Multi-file financial data analysis
- Budgets and savings goals
How SpendDecode works
- Create an account. Sign up without a credit card.
- Upload a statement. Drop in a bank or UPI statement PDF; the AI extracts the transactions.
- AI analysis. A financial health score, spending patterns, anomalies and a category breakdown are generated.
- Personalised insights. An AI financial coach gives recommendations based on the user's real transactions.
- Track progress. Follow the health score over time and work towards savings goals.
Architecture
- Frontend: React web app built with Vite.
- Backend: Python, Django and Django REST Framework APIs.
- Data: Supabase.
- AI layer: LLM integrations built with LangChain behind the insights and the AI coach.
Tech stack
- Python
- Django
- Django REST Framework
- React
- Supabase
- LangChain
- AI integrations
Atharva's role
Founder-led Velquix product — product direction, backend architecture and AI integration.
Current status
Live at spenddecode.velquix.dev with a free plan; paid plans add more AI chats and statement uploads.
Sources
Page updated by Atharva Sonar.
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