Fig. 01
Category mix
Select a category to trace its share of the month.
- Housing: $1,240, 63% share, trend steady.
- Food: $468, 24% share, trend up.
- Transport: $186, 9% share, trend down.
- Subscriptions: $74, 4% share, trend steady.
mega-smart
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Nency Chovatiya
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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Monthly report
Spend, but smarter.
Your categorized expenses, mapped as one month of pattern evidence — where the money actually went, and how the weeks stacked up.
Automatic categorization runs first. The visuals below turn those categories and weekly totals into plain-language patterns you can act on.
Fig. 02
Four-week rhythm
Hover or focus a bar to read that week's total.
Four-week total$1,968Peak · Week 4 $543
Pattern callout
Food is the upward category
$468 sits in Food this month — 24% of the total and the only category trending up, while Housing and Subscriptions held steady and Transport eased off.
Preview dataChanges stay in this preview.
mega-smart AI expense analyzer
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
CATEGORIZETRACKSPOT THE UNUSUALGET RECOMMENDATIONSCATEGORIZETRACKSPOT THE UNUSUALGET RECOMMENDATIONS
How mega-smart thinks
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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