What a financial document analyzer needs to be good at
A general-purpose OCR tool can turn an image into text. That is not the same as analyzing a financial document. A statement has a transaction table with a specific column geometry, wrapped descriptions, page footers, and subtotal rows. A receipt has a vendor block, a set of line items, a subtotal, a tax, a tip, and a total in a specific layout. An invoice has line items, quantities, unit prices, taxes, and a total, plus billing and shipping metadata. Turning any of these into structured data requires more than reading pixels.
Karchu understands the shape of the documents it processes. That means the output is not a text blob to be cleaned up later; it is a row-by-row dataset ready for a dashboard, a spreadsheet, or an accounting import.
Bank and credit card statements
Statement processing follows the same pipeline described on the bank statement analyzer page. Text is extracted (or OCR'd for scanned files), the transaction table is detected, wrapped rows are rejoined, headers and footers are dropped, and every transaction is categorized. Multi-page statements are recomposed. Multi-account statements are split by account.
Receipts and line-item extraction
Receipt analysis surfaces every item you actually bought. Upload a photo or scan and Karchu returns the vendor, the date and time, the subtotal, tax, tip, total, payment method (when present), and every line item with description, quantity, and price. Receipts can be linked to their bank transaction so the books show what the transaction line only summarized. This matters most for expense reporting, reimbursement approvals, tax deductions that need line-item detail (medical, home office, equipment), and audit-ready records for a small business.
Invoices
Invoices follow the same extraction pattern as receipts, with a few additional fields: invoice number, due date, remit-to address, and line-item breakdown. For businesses, invoice extraction turns a folder of paid invoices into a categorized dataset that supports vendor spend analysis, tax reporting, and expense reconciliation.
Batch processing
Analyzing one document is fine. Analyzing twelve months of statements, plus a shoebox of receipts, plus a folder of invoices, in one pass is where the analyzer earns its keep. Karchu accepts batches, merges the extracted data into a single categorized workspace, and lets you export the combined output as CSV or Excel. Duplicates across overlapping documents are detected and deduped. Categories stay consistent across the whole batch because the rule engine is shared.
Privacy and security
Financial documents contain some of the most sensitive information you own. Karchu treats them accordingly. Parsing happens in your browser wherever possible, files are stored in a private vault with row-level security, and no third-party AI models train on your data. See the security page for the full picture.
Frequently asked questions
What kinds of documents does Karchu analyze?
Bank statements (personal and business), credit card statements, brokerage statements, receipts, and invoices. Any document that contains a transaction table or a set of line items can be extracted.
Does it work on scanned documents?
Yes. Karchu uses on-device OCR for scanned PDFs and image files (JPG, PNG, HEIC). OCR runs in your browser, so the file is not shipped to a third-party service.
How is this different from a general OCR tool?
General OCR gives you a text blob. Karchu understands the structure of financial documents. It knows what a transaction table looks like, where the date column is, how to handle wrapped descriptions, and how to identify vendor and line items on a receipt.
Can I extract line items from receipts?
Yes. Upload a receipt and Karchu extracts the vendor, date, subtotal, tax, tip, total, and each individual line item. Receipts can be matched to their transaction row so the books show full detail.
Is my document data private?
Yes. Documents are processed in your browser or in your isolated workspace, files are stored in a private vault, and no third-party AI models train on your data.