From upload to export, every step reads clearly.

Four stages take a raw bank statement PDF and turn it into a clean, downloadable spreadsheet — with full visibility at each point.

Step 01

Validate PDFs on intake

Accept multi-file uploads, reject invalid formats immediately, and keep queue position and progress visible from the moment a file enters the system.

File type rules, size checks, batch status, and status chips all start here. Bad files are flagged before anything enters extraction.

Step 02

Send the uploaded PDF through the parsing layer to isolate text, tables, and candidate transaction rows.

This is where bank-specific logic and OCR can extend the pipeline later without changing the intake or export flow.

Step 03

Clean extracted data into consistent fields — date, description, debit, credit, balance — so output is ready for spreadsheets or downstream systems.

Normalised transactions make CSV and XLSX exports dependable and usable without post-processing.

Step 04

Store converted files, statuses, and timestamps together so every result stays traceable and easy to retrieve.

The same model supports bulk processing and API-based delivery when the platform scales.

Operating principles

Operator-first job flow

The interface shows what is queued, processing, ready, or needs review — so teams stop losing context between upload and export.

Export packaging that feels final

Every successful job can hand back spreadsheet-ready outputs without forcing users to reconstruct files or formats.

Ready for a broader surface

The data model already makes room for team workspaces, billing, API access, and more specialised bank templates.

Ready to run your first batch?

Upload is free to try. No account required for a quick test.