Automating Purchase Order Processing at Scale
How a Global Surface Finishing Manufacturer Automated PO Processing Across 6 Markets with AI
The Challenge
As a global manufacturer serving customers across Europe and the Americas, the company manages a high volume of inbound purchase orders arriving in a wide variety of formats and layouts. The manual effort required to validate, reconcile, and enter each order into the ERP was creating mounting delays, errors, and operational strain across regional teams.
Multiple formats and non-standard layouts
Purchase orders arrived as PDFs, Excel files, scanned images, Word documents, and plain text files, each with its own structure, field placement, and product code conventions.
Time-consuming manual validation
Teams had to manually identify the correct customer record, verify each product code against ERP master data, and re-enter all relevant data line by line. This consumed hours per day across multiple regional teams.
Inconsistent customer and product identifiers
Customers across Europe and the Americas used varying codes and naming conventions, making reliable matching against ERP records impossible without a structured validation layer.
No structured exception handling
When data was missing or inconsistent, there was no systematic workflow to route documents for review, leaving teams to manage discrepancies manually and inconsistently.
Risk of ERP input errors
With high volumes of manual entry, the risk of mistakes reaching the ERP was significant, with downstream consequences for order fulfilment and customer satisfaction.
The Solution
Graip.AI deployed an end-to-end automated purchase order workflow, enabling fast, accurate, and fully auditable PO processing from intake through to ERP posting.
Multi-format document ingestion
The solution automatically ingests purchase orders in all incoming formats, including PDF, DOCX, XLS/XLSX, TXT, and PNG/JPG scans. Each file is classified by type and routed to the appropriate processing flow.
Automated field extraction
Key data is extracted automatically from every document. This includes header fields such as customer details, PO number, date, currency, and commercial terms, as well as line items such as product codes, descriptions, quantities, unit of measure, pricing, and requested delivery dates.
Customer identity resolution
To ensure the correct ERP customer number is used, the solution cross-checks customer names and address details against existing ERP master data. Where a match is unclear or duplicates are detected, the document is automatically flagged for human review.
Item validation against ERP master data
Every product code and line-item detail is validated in real time. Any missing, conflicting, or unrecognized data triggers automatic routing to an exception queue, preventing invalid records from reaching the ERP.
Straight-through processing for clean documents
Documents that pass all validation checks are automatically approved and posted directly into the ERP via API. The original source email and attachments are included with every posting for full traceability.
Human review for exceptions only
Documents that fail validation are presented in a structured review queue with clear flags indicating the reason. Reviewers can correct data directly in the interface, email the supplier to request missing information, or update master data records without leaving the platform.
The Implementation
The solution was delivered through Graip.AI's structured three-phase methodology.
ALIGN (Discover & Blueprint)
Graip.AI worked with the client to gather requirements, identify the highest-value use cases, and define the initial rollout scope, starting with purchase order processing for the UK market.
PROVE (Build, Validate & Launch)
The engagement began with a proof of concept focused on UK purchase orders in PDF format. The PoC achieved over 95% accuracy on the selected dataset. Graip.AI then extended the solution into a production-ready workflow capable of processing purchase orders across all incoming formats, with automated intake, extraction, validation, and exception routing.
SCALE (Measure & Expand)
After a two-week UAT phase, the solution went live and was subsequently rolled out to Finland, the USA, Benelux, Germany, and Scandinavia at an average pace of one country per month.
The Results
The solution delivered significant operational impact across 6 global processing teams.
By replacing manual intake and ERP entry with an automated, validation-first workflow, the organization moved from a reactive, labor-intensive process to a scalable operation where human effort is reserved exclusively for exceptions that genuinely require it.
1,200 documents
1,200 documents per month handled with zero human touch
The Strategic Advantages
Scaling without headcount growth
The organization now handles growing order volumes across 6 markets without proportional increases in processing staff. The same automated workflow operates consistently regardless of volume spikes or market expansion.
Human effort where it matters most
By routing only exceptions for review, teams focus their time on genuinely complex cases rather than routine data entry, improving both job quality and operational output.
Auditability and traceability built in
Every ERP posting is accompanied by the original source email and attachments, creating a complete audit trail without any additional administrative effort.
Conclusion
By deploying Graip.AI across its purchase order intake process, the company transformed a labor-intensive workflow into a scalable, largely automated operation. With 60% of documents now processed without any human involvement and the solution live across 6 global markets, the organization has replaced a bottleneck with a growth engine.
The same framework is now ready to be applied to adjacent back-office workflows, further reducing overhead and enabling the business to scale without the traditional cost of manual administration.
Ready to automate your purchase order processing? Contact us today for a workflow audit.
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