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If running locally, open the file in your browser and go to the Data Files tab to import your CSVs.
If using the server, make sure it is running: node server.js

Top Merchants by total
Spend by Category
Spending by Person Apple Card
Monthly Spend by Account
Details
Net by Month click any month to see all transactions
Subscriptions & Recurring — Status
Spend by Category
vs Prior Month
All Transactions
Spending by Category
Category Trends Over Time
Food & Drink
Shopping — by Merchant
Utilities
Subscriptions
Transportation
Category × Month
Fixed Monthly Bills
Detected Subscriptions & Services
Recurring Costs by Month
All Transactions
Date Account Description Category Type Person Amount
Import a CSV File
Drag & drop CSV files here
or click to browse  ·  supports bank, Apple Card, and Wells Fargo exports
Your files are read locally — nothing is uploaded or transmitted
Supported Formats

Apple Card  — Transaction Date, Clearing Date, Description, Merchant, Category, Type, Amount (USD), Purchased By

Wells Fargo  — no header; columns by position: date · amount · · · description  (auto-detected)

Chase  — Transaction Date, Post Date, Description, Category, Type, Amount, Memo  (signed amount)

Bank of America  — Checking: Date, Description, Amount, Running Bal.  ·  Credit card: Transaction Date, Posted Date, Description, Reference Number, Credits, Debits

Capital One  — Transaction Date, Posted Date, Card No., Description, Category, Debit, Credit

Citi  — Date, Description, Debit, Credit

US Bank  — Date, Transaction, Name, Memo, Amount  (signed amount)

PNC  — Date, Description, Withdrawals, Deposits, Running Balance

Discover  — Trans. Date, Post Date, Description, Amount, Category  (signed amount)

American Express  — Date, Description, Card Member, Account #, Amount  (positive=expense — auto-detected)

Generic bank CSV  — any CSV with recognizable Date + Amount columns; separate Debit/Credit columns also supported

Format is auto-detected from file contents. For Apple Card files, rename to include apple in the filename (e.g. apple_jan_2026.csv) for best results.

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