Invoices, contracts, orders: extracted and entered on their own.
AI reads documents arriving as PDFs and images, extracts structured data (header, line items, amounts, due dates) and writes it directly into the ERP. Audit trail of every decision, human validation only where needed.
What happens today.
Manual data entry of incoming documents (purchase invoices, purchase orders, contracts, delivery notes, receipts) absorbs hours of admin time every week. Transcription errors, accounting delays, invoices paid late because of internal bottlenecks.
Traditional OCR struggles with variable layouts. Modern AI extracts structured data correctly from heterogeneous documents, handles multilingual documents, and progressively learns from cases that required human correction.
Data entry is a tax on time. We can drastically reduce it without firing anyone.
The solution, broken into parts.
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Multi-format AI extraction
PDFs, images, scans, even documents that are not high quality. AI extracts relevant fields (document number, date, VAT ID, line items, totals) and maps them onto your ERP fields.
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Automatic + human validation
High-confidence documents are entered automatically. Medium-confidence ones go to a human validation queue, pre-filled. Threshold configurable based on case risk.
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Direct entry into the ERP
API to the ERP (TeamSystem, Zucchetti, Passepartout, custom). No intermediate Excel exports, no manual upload. The document enters via the channel (email, PEC, upload) and comes out posted in accounting.
The typical profiles who benefit.
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SMEs with more than 200 supplier invoices/month
Document volume justifies automation. Typically human-time savings pay back the investment in 8-12 months.
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Accounting firms with multiple clients
Massive accounting-document handling for dozens or hundreds of clients. AI reduces the data-entry load on junior staff and frees time for high-value activities.
Transparency on what the client does.
Before we start we need a few accesses and decisions. All reasonable, no surprise asks.
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Training documents
- 100-300 sample documents per category (invoices, orders, contracts), anonymized
- Field mapping: how this data should be written to your ERP
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Technical access
- API write access to the ERP
- Document ingress channel (dedicated email, PEC, shared folder)
Indicative numbers, not quotes.
- TIME
- Typically 8-14 weeks from discovery to go-live. Single-case scope (e.g. only supplier invoices) possible in 6 weeks.
- COST
- Range €20,000-60,000 for the initial version. LLM/OCR cost €0.02-0.15 per processed document.
- MODEL
- Fixed milestones. Soft launch on a document percentage, progressive scaling.
Indicative numbers. For an accurate quote, let's talk.
Answers to the most common questions.
Does it work with Italian XML SDI electronic invoices?
Italian XML SDI electronic invoices are already structured, so they do not need AI: they are parsed directly. AI automation is for supplier invoices received in PDF/paper format (frequent from foreign suppliers, receipts, till receipts, purchase orders, contracts).
How accurate is AI extraction?
On typical documents (Italian invoices, orders, standard contracts) accuracy exceeds 95% on main fields (total, VAT ID, date, due date). On line items accuracy is 85-95% depending on document quality. Low-confidence cases are sent to human validation, never entered unchecked.
What happens if AI posts an invoice wrong?
Every processed document has an audit log: original document, extracted data, confidence level, any human correction. Errors are spotted at reconciliation (cross-check with the ERP and bank statement). The workflow is designed to be reversible and traceable, not a black hole.
Recognize your case?
Write a couple of lines about your context. We'll reply within 24-48 hours with an initial assessment and a first orientation on time and cost.
Let's talk