Handle supplier exceptions at a scale previously reserved for the top of town.

Supply Chain Exception Management is an AI orchestration layer that sits on top of your ERP, supplier portals, and shipment feeds, detects exceptions as they happen, and routes them to your procurement team as a prioritised queue with recommended actions. It is built for mid-market wholesalers, manufacturers, builders, and healthcare groups whose procurement team spends half the week chasing suppliers.
Coles and Bunnings run supplier exception management with 50-person teams and bespoke platforms that cost millions. That was the only way to do it properly. Until recently.
Most mid-market procurement teams run the same process with four people and an inbox. A shipment is late. A price on the invoice does not match the PO. A box arrives with the wrong part number and nobody flags it until production stops. The signals are all there, scattered across the ERP, the supplier portal, a freight tracker, and the email thread with the rep. Nobody has time to stitch them together before the problem lands in the warehouse.
The cost is invisible until you look. Half a buyer's week goes on chasing. A stock-out on an A-line costs more than the buyer's salary. A freight cost blow-out nobody caught eats the margin on the quarter. The team is not bad at their job. They are running an exception-handling operation with no exception-handling system.
The exception detection agent reads from SAP Business One, NetSuite, Pronto, or Microsoft Dynamics, alongside your supplier portals and the carrier feeds from Toll, StarTrack, or whoever moves your freight. It matches shipment data against POs in near-real-time. When something breaks the rules you set, it writes a case, attaches the context (the PO, the supplier, the last three exceptions from the same vendor, the downstream impact on production), and drops it into a queue ranked by cost and urgency.
Your head of procurement opens one screen in the morning. Twelve exceptions. The top three have recommended actions already drafted. Approve, adjust, or reject. The approved action writes back to the ERP. The team is negotiating by 10am, not chasing until 5pm.
Discovery maps your exception types, signal sources, and the approval rules that already live in people's heads.
We connect to your ERP, supplier portals, and shipment feeds through the AIS without disturbing the source systems.
The detection agent runs against live data. Every exception gets a case with cost impact and supplier context attached.
Cases land in a prioritised queue. Recommended actions are drafted from your historical playbook.
Your procurement team approves, adjusts, or rejects. The action writes back to the ERP automatically.
Outcomes feed back into the model. The queue gets sharper on your exceptions every month.
| Exception type | Signal source | Recommended action | Who approves |
|---|---|---|---|
| Late shipment | Carrier feed vs PO ETA | Chase supplier, flag downstream stock risk | Buyer |
| Short delivery | Goods receipt vs PO quantity | Raise credit, trigger backorder, alert warehouse | Buyer |
| Price variance vs PO | Invoice vs PO line | Hold invoice, request credit note | Accounts payable lead |
| Quality fail | QA log vs inbound batch | Reject batch, log supplier defect, raise RMA | QA manager |
| Substitute part delivered | Goods receipt vs PO SKU | Accept with engineering sign-off or reject | Head of procurement |
| Early delivery, no storage | Carrier ETA vs warehouse capacity | Defer inbound or arrange overflow | Warehouse manager |
| Supplier invoice mismatch | AP system vs ERP | Query supplier, hold payment | Accounts payable lead |
| Freight cost blow-out | Freight invoice vs quoted rate | Challenge invoice, re-tender lane | Head of procurement |
Exceptions that used to surface three days after the shipment arrived now land in the queue within minutes of the signal. Procurement acts while the supplier can still fix it.
Every exception is logged, costed, and attributable. Annual contract reviews stop being a feelings conversation and start being a spreadsheet with the vendor's name on it.
Typical teams reclaim 30 to 50% of the buyer week previously spent stitching systems together. That time goes into supplier negotiation, category strategy, and the work nobody has got to.
Catching a short delivery on Monday morning, not Thursday afternoon, is the difference between a phone call and a production halt. Downstream disruption drops measurably inside a quarter.
Production-ready AI agents, chatbots, and multi-agent systems, built senior-led end-to-end.
Learn moreThe operating layer your AI, automation, and analytics run on. Deployed in two weeks.
Learn moreClose the gap between what your data knows and what your business does. The architecture from insight through decision to action.
Learn moreSKU-level demand forecasts that feed replenishment directly, so planners manage exceptions instead of rebuilding spreadsheets every Monday.
10–20%
reduction in working capital tied to inventory
Read, extract, and post the document. Leave the humans to handle the exceptions.
60-80%
reduction in manual document-handling hours
An automated intelligence layer deployed into your business in two weeks. Your AI agents, dashboards, and automation run on it from day one.
2 weeks
to AIS live with first source systems
30-minute call, no slides, no obligation. We'll tell you plainly whether this is the right fit for what you're trying to do.
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