FRoSTA: Pioneering touchless invoice processing and increasing the automation rate in the procure-to-pay process
FRoSTA AG· GermanySAP Build Process Automation · SAP Document AI · SAP S/4HANA Cloud Private Edition +2
FRoSTA AG, a frozen food manufacturer with about 1,850 employees and production facilities in Germany and Poland, automated its supplier invoice processing using SAP Build Process Automation and the premium, LLM-based edition of SAP Document AI on SAP Business Technology Platform. Previously, each of FRoSTA's roughly 30,000 annual invoices for goods received was manually touched at least three times, with approvals delayed by up to two weeks when managers were traveling. The new automation monitors incoming documents, uses an LLM in SAP Document AI to extract and classify invoice data regardless of format or language, validates it against SAP and third-party systems, and creates the invoice in SAP S/4HANA Cloud Private Edition, routing exceptions to an approval workflow accessible via the Joule Work mobile app. It now takes a minute to process an invoice, from arrival to posting, 70% of automated invoices are booked without any human touch, and about 60% of the 30,000 annual goods-received invoices are processed automatically with no human intervention. The project went from ideation to go-live in three months, built primarily by an IT trainee with no programming background, with implementation support from SAP partners sovanta AG and Amista.
Overview
FRoSTA AG, a frozen food manufacturer with about 1,850 employees and production facilities in Germany and Poland, automated its supplier invoice processing using SAP Build Process Automation and the premium, LLM-based edition of SAP Document AI on SAP Business Technology Platform. Previously, each of FRoSTA's roughly 30,000 annual invoices for goods received was manually touched at least three times, with approvals delayed by up to two weeks when managers were traveling. The new automation monitors incoming documents, uses an LLM in SAP Document AI to extract and classify invoice data regardless of format or language, validates it against SAP and third-party systems, and creates the invoice in SAP S/4HANA Cloud Private Edition, routing exceptions to an approval workflow accessible via the Joule Work mobile app. It now takes a minute to process an invoice, from arrival to posting, 70% of automated invoices are booked without any human touch, and about 60% of the 30,000 annual goods-received invoices are processed automatically with no human intervention. The project went from ideation to go-live in three months, built primarily by an IT trainee with no programming background, with implementation support from SAP partners sovanta AG and Amista.
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Inspect the highlighted sourceThe challenge
FRoSTA processes around 30,000 invoices for goods received each year in Germany. Staff in accounting had to manually scan incoming documents, seek budget approval from relevant stakeholders, and post documents to the company's ERP software, with each document touched at least three times before entry, and approvals could be delayed by up to two weeks when managers were traveling.
The solution
FRoSTA selected SAP Build Process Automation and the premium, LLM-based edition of SAP Document AI on SAP Business Technology Platform to automate the processing of paper, PDF, and Microsoft Excel-based invoices. The automation monitors a folder for incoming documents, uses an LLM in SAP Document AI to extract and classify invoice data regardless of format or language, validates the extracted information against SAP and third-party systems, triggers an approval workflow if necessary, and creates the invoice in SAP S/4HANA Cloud Private Edition, with cost-center leads reviewing approvals via the Joule Work mobile app.
Reported business value
It now takes a minute to process an invoice, from arrival to posting, 70% of automated invoices are booked without any human touch, and about 60% of the roughly 30,000 annual goods-received invoices are processed automatically with no human intervention. The project went from ideation to go-live in three months.
Sources
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