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PDF, email, image, XML, EDI — every invoice format parsed, validated, matched to PO, and posted to SAP MIRO automatically. No templates. No manual re-keying.
Step 1
Invoice received via email, EDI, API, or file upload — any format, any source.
Step 2
AI models extract header data, line items, tax, payment terms, and supplier reference — without predefined templates.
Step 3
Extracted data validated against SAP vendor master, PO data, and business rules — flagging discrepancies before posting.
Step 4
2-way and 3-way PO matching against SAP purchase orders and goods receipts — automated tolerance checking.
Step 5
Matched invoices posted directly to SAP MIRO — creating FI documents, updating PO history, and triggering payment.
Step 6
Unmatched or failed invoices routed to exception queue with AI-generated reason codes — reviewed and resolved by AP staff, not re-keyed.
Structured PDF invoices with embedded text are parsed directly — header, line items, tax, payment terms, and supplier details extracted without OCR.
Scanned paper invoices converted to image format are processed through OCR + AI extraction — handling poor scan quality, rotated documents, and varied layouts.
Invoices received as email attachments — PDF, Word, or image — are ingested from a monitored mailbox and processed automatically without manual forwarding.
Photo or scanned invoices in image formats are processed through the AI extraction pipeline — tolerating varied quality, layouts, and languages.
Structured XML invoices (including UBL, PEPPOL, and supplier-specific formats) are mapped to SAP MIRO fields without manual interpretation or format-specific templates.
EDI invoice messages (INVOIC, X12 810, and similar) are received, parsed, and mapped to SAP document fields — handling standard and variant EDI implementations.
AI models adapt to supplier invoice layouts without predefined templates — no setup time per supplier, no template maintenance as layouts change.
Automatic matching of invoice amounts to SAP purchase order lines, with optional 3-way matching against goods receipts — applying your configured tolerance rules.
Validated invoices post directly to SAP MIRO — creating financial documents, updating PO history, and triggering payment runs without AP involvement.
Exceptions are surfaced with AI-generated reason codes and suggested resolutions — AP staff review and approve, not re-key from scratch.
Full processing audit trail from receipt to posting — source document, extraction output, validation results, match decisions, and SAP document number.
Integrates with SAP ECC 6.0 and S/4HANA via BTP — the same AI processing pipeline works across both landscapes.
Key Metrics
PDF (native and scanned), email attachments, JPG/PNG/TIFF images, XML (including UBL, PEPPOL, and supplier-specific formats), and EDI (INVOIC, X12 810, and variants). No template configuration is required — the AI adapts to each supplier format.
Extraction accuracy depends on document quality and format consistency. For clean, digital PDFs from established suppliers, field-level accuracy exceeds 95%. Scanned or low-quality documents have higher exception rates and route to the human review queue. The AI extraction is always validated against SAP data before posting — mismatches are caught in the validation step, not discovered post-posting.
Yes. The AI invoice processing integrates with standard SAP MIRO — creating standard FI documents and updating PO history as if manually entered. Your existing MIRO configuration, tolerance levels, and approval workflows are preserved.
Invoices that cannot be automatically matched are routed to an exception queue with AI-generated reason codes (e.g., "PO quantity exceeded", "supplier not found in vendor master"). AP staff review exceptions and take action — they do not re-key the invoice from scratch.
Cost reduction comes from three sources: eliminating manual data entry per invoice, reducing the exception rate through automated PO matching, and reducing AP staff time per invoice from minutes to seconds for the automated volume. The actual reduction depends on your current process and invoice volume — we scope this during discovery.
Failed extractions are captured with the original document and processing log. AP staff can review the original, correct extracted fields, and approve for posting — the system learns from corrections to improve future extraction.
Talk to a specialist about your current AP process. We'll show you exactly how AI invoice processing integrates with your SAP landscape.