AI categorisation of receipts in Yuki or Klippa, how far can I trust it?
AI classification is good in 80-90 percent of cases, but errors often sit in VAT rate and 'looks like category X but is Y'. Treat as suggestion, not truth.
Try this first
- 1Let AI suggest but approve per receipt, at least for the first 2 months, to train the layer honestly.
- 2Enable VAT detection but verify per receipt, a 9 percent till receipt booked as 21 percent is a common error.
- 3Keep categories small and clear, an 80-account chart drifts more than a 25-account one.
- 4Open a top-errors report each quarter and feed back in the package, this notably improves classification.
- 5When in doubt book manually, not 'we will fix later', that moment rarely comes.
When to bring us in
For an audit of AI classification and impact on your VAT return, we can measure it.
See also
- Switching from Exact Online to Yuki, open items and history do not matchPackage migrations stumble on ledger mapping and open AR/AP. Without a mapping table you lose context.
- Twinfield to Exact, dimensions and cost centres go missingTwinfield uses dimensions, Exact uses cost centres and projects. The mapping is not one-to-one.
- Accountant asks for RGS mapping, your ledger does not follow RGSRGS is the Dutch standard chart that SBR filings and accountant software expect. Without mapping, every year-end is manual.
None of the above fits?
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