Reuse a client's confirmed mapping so matching accounts skip re-review. You can leave this on "Categorise fresh" — after processing, we'll spot a matching saved mapping and offer it automatically.
Off by default. When on, only account names and balances are sent — never transactions, and never figures it can change. All figures remain computed by deterministic code.
Processing… large ledgers can take a moment.
Set up a new format
Upload a sample export, confirm the columns, and save it as a reusable format. Nothing is saved until it parses cleanly.
Use the real file you want to onboard — the whole thing, so totals can be checked. PDFs must be text-based (digitally generated); scanned/image PDFs aren't supported yet.
Optional. Only column headers + a few sample rows are sent — never figures.
Reading the sample…
Confirm the columns
match each field to a column from your file
Parsing & reconciling the sample…
Set up a report-style format
For exports that aren't a simple table — per-account sections, sub-totals, headers mid-file. The AI drafts a parsing config from a sample; you confirm it parses, then save. Nothing is saved until debits equal credits.
Use the real file you want to onboard — the whole thing, so totals can be checked. Only structure (labels + a few sample rows, figures masked) is sent to the AI — never the numbers.
Drafting a parsing config…
Review the parsing config
the AI's draft — tweak if a row is misread, then check it parses
Parsing & reconciling the sample…
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Categorisation
click a line to expand · tick ☑ any line or bucket to give it its own tab ·
Save this client's confirmed account mapping so next period's file is auto-categorised — matching accounts skip re-review. Next upload, just process the file: we'll spot the match and offer it automatically (or pick it under Advanced options → Saved account mapping).
Every figure is extracted by deterministic code and reconciled against the file's own totals. The categorisation is a starting point for analysis — a human should review it before it is relied upon.