Exploring an Agentic App for Procure-to-Pay EDI
I’ve been thinking about this idea for a while now: what if the teams who live inside EDI transactions every day — buyers, warehouse staff, AP clerks, and the analysts who keep the pipes flowing — had one place to see the entire procure-to-pay chain, instead of stitching together status from five different screens?
Most organizations run EDI 850 (purchase orders), 855 (acknowledgments), 856 (ship notices), and 810 (invoices) as separate transaction types, each landing in its own queue, with its own error codes, and often its own team watching it. When something breaks — a vendor part number that doesn’t match, a PO line that’s been closed or cancelled, a receipt that blows past tolerance — nobody has a single view of what happened, who’s supposed to fix it, or whether it’s even the kind of thing software can fix on its own.
So I put together a general mockup of what an agentic command center for this problem could look like: one workspace that tracks a transaction from the moment a PO is issued through acknowledgment, shipment, and invoice, and surfaces exceptions the moment they hit the open interfaces — with the option to resolve them inline, or escalate them to the right team, instead of waiting for someone to notice.
A few ways different roles might use something like this:
- An EDI Application Analyst gets the full technical picture — every transaction type, every interface error, with root cause and resolution status in one table.
- A Procurement Buyer sees just the exceptions that need a buying decision — a mismatched vendor part number needing a change order, a cancelled line, a closed PO — without wading through routine receiving noise.
- A Warehouse Manager filters down to receiving-side exceptions only: what’s stuck, what shipped clean, and what a carrier or quantity issue is blocking.
- A Payables Clerk sees invoice-side exceptions specifically — price or UOM mismatches, duplicate invoices, three-way-match failures — and whether they can be auto-corrected or need a hold.
It’s still early — more a thought experiment in interface design than a finished product — but it’s been a fun way to work through what “agentic” actually means for a process as unglamorous and essential as EDI exception handling.
Disclaimer: All data shown in this mockup — purchase orders, vendors, transaction amounts, error records — is synthetic sample data generated for demonstration purposes only. It does not reflect any real company, supplier, or transaction, and this project is solely intended to explore and showcase the capabilities of agentic AI applications in an enterprise workflow context.