Matching invoice and PO lines without rules, tables, or a perfect description match, with 100% confidence

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Invoices that read differently than purchase orders are impossible for rules-based systems to reconcile. Only AppZen AI reads and understands the content and context of invoices and POs to guarantee 100% accurate matching–even when items and descriptions are different.

Is the complexity of PO matching holding you back?


With AI doing the work of AP processing, we were able to increase the efficiency of our AP team by 70% and reduce our FTEs.”


Complex invoice matching requires a person to read POs and invoices and decide whether line items and descriptions are equivalent. Rules-based solutions can’t handle these situations:

  • Line item descriptions that are a fuzzy match between invoices and POs
  • Invoice lines that need to be combined to correctly match PO lines
  • Invoice line amounts that need to be matched based on department codes on a PO
  • Identifying purchase order lines to match, even when they lacks sufficient funds

Processing PO-backed invoices requires you to check every line item to confirm they follow the purchasing details of the PO. Rules-based systems rely on an exact match or a cross-reference table to translate specific invoice values.

Every time you have to contact the buyer or use your expertise, focus, and time to read and interpret documents, the 3-way match is held up. Hours and even days of your time are lost.



Fully-automated identification without rules, tables, or an exact PO match

AppZen’s Autonomous AP is uniquely capable of intelligently predicting which PO lines should match against which invoice lines, even when they’re out of order, the items and descriptions are different, or they have to be grouped together. Its match is not dependent on rules or cross-reference tables.

Even when the PO is out of funds, Autonomous AP can still confirm matching line items and will automatically flag the appropriate buyer. It then continuously rechecks the system until requirements have been met, then completes the match process without any additional action from you.

AppZen’s AI models have the extensive finance domain expertise of an AP team with years of experience processing your invoices. Using this AI knowledge and historical insight from your invoice documents, purchase orders, chart of accounts, suppliers, and more, it can interpret your spend data with 100% guaranteed accuracy. No human review is required. The AI also continuously learns from user feedback and downstream transaction changes. This allows it to improve its future predictions, increasing the number of invoices that can be fully automated and require zero human touch.

AI first is rare. A lot of legacy companies have their standard OCR solution that they're bolting on [AI] and it's maybe improving things, but it's not a true, AI-first model.



7 days






Increased efficiency with Autonomous AP

Reduced headcounts are adding pressure to the already heavy workloads of most AP teams. AppZen makes it easy to transition to zero-touch invoice processing with fewer resources.



A leading provider of industrial technologies and supplies processing 300K invoices annually took 5 business days to move those invoices their inbox to ready-to-pay. Their current solution only captured invoice header information and was highly error-prone. While 97% of their invoices were PO-based, because of variations between invoices and POs, the majority had to be manually reviewed and matched. They wanted to be able to process each invoice within 1 day. The only way to do that with their current solution would have required them to add additional headcount.



The day they went live, Autonomous AP integrated with their SAP instance, it immediately started learning how invoices were historically matched. The AI models are able to match over 50% of even their complex invoices to POs without manual review or adding any AP processors. BONUS: They’re also benefitting from accurate, automated GL code prediction.

Empowering over 1,000 finance teams