mega-smart
Nency Chovatiyai want to build smart expense analyzer Smart Expense Analyzer is an AI-powered personal finance application that analyzes a user's expenses and provides meaningful spending insights. It automatically categorizes transactions, tracks budgets, identifies unusual spending using Machine Learning (Isolation Forest), and generates simple AI-based recommendations. The system uses Python, FastAPI, SQLite, Streamlit, Pandas, Plotly, and LLMs to provide an interactive and intelligent expense-management experience.
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Set it · Watch it · Adjust it
Budgetsthat hold
Set your targets
Name a target, pick the period, then compare it against actual spending as the numbers come in.
Create a target
Budget toolsA budget target pairs an amount with a period. Once saved it appears in the comparison collage with its progress against actual spending.
Saved budgets are stored with your account and shared with every view that reads this collection.
Actual spending is matched against each target as expenses come in.
Actual vs target
0 budget targets tracked
No budget targets yet
Nothing is being tracked for this account. Create your first target with the form alongside and it will appear here with its progress against actual spending.
SpendSmarter.
- Automatic transaction categorization powered by AI
- Real-time budget tracking against your targets
- Unusual-spending detection with Isolation Forest
- Simple AI-based recommendations for smarter spending
Four ways mega-smart makes sense of your money
From the moment a transaction lands, mega-smart categorizes it, checks it against your budgets, watches for anything strange, and turns the patterns into recommendations you can use.
Auto-Categorized
Every transaction is sorted into a spending category automatically, so you always know where the money went without lifting a finger.
Budget Tracking
Set targets per category and watch a live gauge show how close you are to the line before the month runs out.
Isolation Forest Detection
A Machine Learning model flags spending that breaks your normal pattern, so surprise charges get surfaced fast.
AI Recommendations
LLM-informed suggestions translate your patterns into plain-language moves you can actually act on.
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