Start with the problem.
Manual re-entry is repetitive, but an extracted amount or supplier name can be wrong. This design combines extraction with business validation and a review queue, treating the model's output as a proposal until approved.
A practical way forward.
Document intake
Capture authorised files, retain the source and identify duplicates before extraction.
Business checks
Match supplier and item references, compare totals and taxes, and flag uncertain or inconsistent fields for staff review.
Controlled ERP posting
Create a draft through an authorised API, preserving who approved it and how the source maps to the final transaction.
The workflow, simply.
- Receive document
- Extract & validate
- Staff approval
- ERP draft or posting
Architecture to consider.
A protected document store holds source files with access and retention rules.
OCR or multimodal extraction feeds a schema-validated candidate record.
ERP adapters apply approved changes with duplicate protection and an audit reference.
How success should be tested.
- Measure field-level accuracy across representative document layouts.
- Test duplicate documents, tax mismatches and unknown suppliers.
- Verify rejected or unapproved records cannot post to the ERP.
Useful things to know.
Can AI enter supplier invoices directly into an ERP?
It can prepare candidate data and, where explicitly authorised, submit an approved transaction. The proposed workflow validates references and totals and requires staff review for exceptions.
What data is needed for a pilot?
Use permitted sample documents that cover common suppliers, formats and difficult cases, with corrected reference values. Remove unnecessary personal data and define where files and model requests are processed.
