AI Invoice-to-PO Line Matching · SAP
Solving the last mile of invoice-to-PO line matching.
Traditional ERPs match invoices at the Purchase Order level. Intwise identifies the exact Purchase Order line automatically — using semantic AI, business rules, and confidence scoring — so your AP team stops guessing which line an invoice actually belongs to.
The Problem
The last mile problem
Most UBL 2.1 and Peppol BIS 3.0 e-invoices carry a Purchase Order number at the header level — never the PO line. Everything after that is manual.
The invoice XML tells you the PO. It does not tell you the line. So an AP processor opens the PO, and manually compares every candidate line against the invoice, one field at a time:
- Description
- Quantity
- Material / SKU
- Unit Price
- Tax Code
Multiply that across every invoice referencing a multi-line PO, every day, every AP clerk.
Hours wasted every week — on a lookup an ERP should already know.
The Solution
How Intwise works
A seven-step pipeline that turns an ambiguous invoice line into a ranked, auditable PO line match.
Invoice XML
UBL 2.1 / Peppol BIS 3.0 e-invoice received, referencing one or more SAP purchase orders.
Extract Invoice Lines
Line-level description, quantity, unit price, material and tax data are parsed out.
Retrieve SAP PO
All candidate lines are pulled from the referenced SAP MM purchase order(s).
AI Similarity Engine
Each invoice line is embedded with SBERT and scored against every PO line candidate.
Confidence Ranking
An 8-feature weighted scorer ranks candidates and assigns a confidence percentage.
Review if Required
Sub-90% matches route to an AP reviewer with the ranked candidates and their scores.
SAP Posting
The resolved line match is emitted as a simulated SAP INVOIC02 IDoc, ready for posting.
Capabilities
Built for line-level accuracy
Semantic understanding, grounded by the business rules an AP auditor would actually apply.
Semantic Similarity
Sentence Transformer embeddings compare meaning, not just keywords.
Business Rules
Quantity, price, and material-code validation layered on top of the AI score.
Material Matching
Cross-checks SKU and material master data against invoice descriptions.
Confidence Score
Every match carries a transparent, weighted percentage — never a black box.
Human Review & Audit Trail
Sub-threshold matches queue for review, with every decision logged.
SAP Integration Suite
Designed to sit alongside SAP S/4HANA and BTP integration flows.
Triage
Three confidence tiers
Every match lands in one tier, so AP teams know at a glance what needs their attention.
Architecture
Where Intwise sits
A model-as-a-service layer between the invoice and SAP posting — not a replacement for either.
Interface
Inside the matching UI
A React 19 + Vite simulation UI, built to demonstrate the full workflow end to end.
Dashboard
Queue overview by confidence tier.
Invoice Upload
Drop an XML invoice to kick off matching.
Matching Results
Ranked PO line candidates with scores.
Review Screen
Side-by-side line comparison for reviewers.
Analytics
Match-rate trends across confidence tiers.
What It's Built For
Designed to remove the manual step
Intwise is a Phase 1 proof of concept: the scoring weights above are hand-tuned as a stand-in for a trained ranker, there's no feedback-learning loop yet, and SAP posting in the demo is simulated rather than live — noted here rather than glossed over.
SAP Community
Read the complete technical blog
Learn how Intwise approaches one of SAP's persistent procurement problems — AI-powered, line-level invoice matching, explained end to end.