AI-powered invoice processing with accountant oversight
A controlled workflow for extracting data from handwritten, international and Hungarian electronic invoices, including NAV XML and approval by an accountant.
Invoice processing combines high volume with a wide range of document formats. Handwritten invoices, scans, international supplier documents and Hungarian electronic invoices all present different extraction and validation problems.
A controlled AI agent can prepare structured data and highlight uncertainty, while the accountant remains responsible for interpretation and approval.
The starting problem: many invoice types and extensive manual entry
Accountants repeatedly transfer invoice numbers, dates, supplier data, tax amounts and currencies. International layouts and terminology vary, while small OCR errors can alter a critical field.
- Manual entry consumes specialist time
- Foreign invoices differ from familiar Hungarian formats
- Scans and handwriting create uncertain characters
- Errors often appear only during later checks
The solution: an invoice-reading agent under accountant control
The agent first identifies the document type and selects the appropriate extraction method. It creates a standard record regardless of the source format and attaches confidence or validation information to important fields.
- Handwritten and scanned invoices
- International supplier invoices
- Hungarian electronic invoices and embedded data
- A review interface for accountant approval
What happens to an incoming invoice?
The workflow classifies the file, extracts the essential fields and compares values that should reconcile. Suspect fields are presented first so the reviewer can focus attention where it matters.
- Detect whether the source is an image, PDF or electronic invoice
- Extract the invoice number, parties, dates, net, gross and tax amounts, and currency
- Validate totals and required fields
- Flag low-confidence values and exceptions
NAV XML: do not rely on the image when structured data exists
Hungarian electronic invoices may contain NAV XML data that is more reliable than reading the visual representation. Where available, the agent locates and parses this structured content, while still presenting the document for comparison.
An important boundary: AI assists, the accountant decides
The agent does not determine final accounting treatment or tax compliance. It prepares data, applies mechanical checks and makes uncertainty visible. The accountant confirms the record and exercises professional judgement.
How does this improve everyday accounting work?
The workflow reduces data-entry interruptions and creates a more consistent queue across mixed document types. Accountants spend a greater share of their time reviewing exceptions and making professional decisions.
- Faster extraction across mixed formats
- Less manual typing
- Uncertain fields are easier to review
- More consistent preparation across countries and suppliers