Not based on a specific customer deployment. The company, figures, decisions, and outcomes below are a constructed example that shows how Intended’s mechanism applies to this kind of problem. They are not measured results from a named customer. Where we publish a real, attributed customer outcome, we will say so explicitly.
Governing Supply-Chain AI Procurement Decisions
Consider a global manufacturer whose AI agents manage procurement, inventory optimization, vendor payments, and logistics coordination across many factories and countries, with purchasing in SAP S/4HANA and Oracle Procurement.
01 · the challenge
The kind of problem this addresses.
02 · how it works
See the difference.
AI agent: reorder raw materials
Steel alloy, Qty: 50,000 units
Selects vendor
Cheapest option, not on approved list
Creates purchase order
No budget validation, no approval
PO submitted
$320,000 committed without review
03 · the solution
What they deployed.
- — Policy rules for procurement, inventory, and logistics actions
- — Vendor allowlist rules by material category and factory location
- — The agent sends the PO's budget line and remaining budget with each request, and policy checks them before anything is committed
- — Agents call Intended through the SDK before acting in SAP S/4HANA, Oracle Procurement, or the internal logistics APIs, and act with their own credentials only after an ALLOW and a signed authority token
- — Intended decides and signs; it never holds the manufacturer's ERP credentials. The ERP integration layer can verify each token offline before it creates a PO
- — Thresholds: auto-approve < $100K from Tier 1 vendors, escalate all others
- — The agent sends each order's deviation from its historical average; policy escalates anything more than 30% off
04 · implementation
From zero to governed.
Week 1-2
Map
Catalogue the AI procurement agents and the vendor and ERP systems each one touches.
Week 3
Integrate
Add the SDK call ahead of the agents' SAP, Oracle Procurement, and logistics API actions, and token verification in the ERP integration layer.
Week 4
Configure
Write vendor allowlists, budget thresholds, and quantity guardrails. Check them with policy simulation.
Week 5
Enforce
Enable enforcement across all factories. Off-list vendors are denied before a PO exists.
05 · illustrative outcomes
What this is designed to deliver.
Modeled figures for this scenario — what the workflow above is built to achieve, not measured results from a named customer.
0%
POs vendor-checked
Against the approved vendor allowlist
0%
POs validated against budget
Budget fields checked by policy first
0%
Decisions evidenced
Vendor, budget, and approval in the chain
>0%
Quantity-anomaly flag
Orders deviating from historical norms escalate
06 · decision replay
Example decisions, full trace.
Sample decision records that show the shape of the evidence Intended produces. Illustrative, not drawn from a live customer’s logs.
supply.procurement.purchase-orderRISK: 18/100ALLOWReorder steel alloy bolts, Qty: 10,000 from FastenerWorld (Tier 1 vendor)
Resolved by: Policy: auto-approve < $100K, Tier 1 vendor, within quantity norms
supply.procurement.purchase-orderRISK: 88/100DENYOrder custom circuit boards, Qty: 500,000 from NewTech Ltd (not on vendor list)
Resolved by: Policy: vendor not on approved list for electronics category
supply.inventory.rebalanceRISK: 14/100ALLOWTransfer 5,000 units of packaging material from Factory 7 to Factory 3
Resolved by: Policy: inter-factory transfers auto-approved for non-critical materials
supply.procurement.purchase-orderRISK: 72/100ESCALATEEmergency order: 200,000 microcontrollers from ChipDirect (Tier 2), $890,000
Resolved by: VP Supply Chain (approved the emergency order with a budget exception)
the takeaway
AI procurement agents often act without domain awareness. Authority guardrails that encode how a supply chain actually works — vendor tiers, budget cycles, quantity norms — turn each purchase order into a checked, evidenced decision instead of an unreviewed commitment.
Why this pattern matters — not a customer quote.
Start governing AI procurement
Free to start. See every AI decision from day one.