SAP AI Agent · PP · MM · MRP Demo available
Illustrative example · not a production transaction
Why it matters
Planners face thousands of messages in MD04 and MD06 every morning, chase suppliers by email and fix the same problems again after the next run.
How it works
The same four steps as every Artificio agent. The agent does the research and the paperwork; your teams make the decisions.
After each MRP run, every exception message with its demand and supply.
Finds the document behind each message and checks current stock, orders and lead times.
Picks the best action and asks the supplier to confirm where needed.
Writes the approved change and checks the result after the next run.
Worked example
The overnight MRP run flags a purchase order that is needed six days earlier for a customer order. Here is what the agent works out before the planner logs in.
Without a change, sales order 1100457 is short on its requested date. Plant 2000 has 400 EA, which is not enough on its own.
| Option | Result | Why |
|---|---|---|
| Pull PO in to 13 Nov | Covers all | Needs supplier confirmation; recommended |
| Transfer 400 EA from plant 2000 | Short 450 EA | Partial cover; plant 2000 needs stock on 25 Nov |
| Leave as is | Short 850 EA | Customer order 6 days late |
| Supplier answer | 13 Nov confirmed | Midwest Steel replied in 3 hours |
| Next step | Change PO date | Needs the buyer's approval |
The PO date changes in SAP only after the buyer approves. After the next MRP run, the agent checks that the exception is gone and no new shortage appeared.
Illustrative example · names and values are fictional and depend on your SAP configuration
Inside the platform
The case shows who it is waiting for, what happens next, what the agent checked and exactly what each person is approving.
Waiting for M. Patel (Buyer, P02) to approve moving PO 4500018832/10 to 13 Nov, asked Mon 2 Nov at 09:41.
A reminder goes out at 13:41 today. The agent checks the result after tonight's MRP run.
| Step | Owner | Status |
|---|---|---|
| Diagnosis and projection | Agent | Done |
| Supplier confirmation | Midwest Steel | Confirmed |
| PO date change | M. Patel · Buyer | Waiting |
| Verify after MRP run | Agent | Scheduled |
Move PO 4500018832/10 from 19 Nov to 13 Nov? Midwest Steel confirmed the earlier date in writing.
Recreation of the Artificio case screen · names and values are fictional
Capabilities
Every exception message gets the right next step, confirmed with the people and suppliers involved.
Ownership
You assign owners by MRP controller, purchasing group or plant. Whoever answers first decides, and anything without an owner goes to the planning lead.
Owners, rules and tolerances are configured to your organization and agreed for each deployment.
Controlled autonomy
The agent proves itself on your real work before it writes anything to SAP. The platform measures how often your people agree with it, so you decide when to give it more room, case type by case type.
The agent proposes every action but writes nothing to SAP. Your people decide, and each answer counts toward the agreement rate.
The required owners approve. The agent acts in SAP only when the last approval lands.
For case types you explicitly configure and approve, such as pushing out purchase orders within an agreed supplier window, the agent acts on its own and reports back.
Governed agent runtime
What makes this agent different is its configuration: its instructions, the tools it may use and the policies it works under. Reviewers, approvals, versions and audit work the same way for every agent you add.
Decisions go to named owners or authorized teams, with reminders, and every email links back to the case.
Gathering data is kept separate from changing SAP. Action tools are controlled and can require human approval before they run.
Versions can't be edited, and each case keeps the version it started with, so a change never alters work in progress.
Recreations of Artificio platform screens
What we measure
Every pilot tracks the same four measures from day one, so the business case comes from your data, not ours.
For SAP teams
The agent reads and writes data through supported SAP interfaces, without modifying standard SAP objects and without replacing your existing governance.
| MRP results | Exception messages, demand and supply |
|---|---|
| Purchasing | PO lines, confirmations and suppliers |
| Production | Planned and production orders |
| Stock | Plant stock and in-transit quantities |
| Purchase orders | Approved dates and quantities through supported interfaces |
|---|---|
| Planned and production orders | Approved date and quantity changes |
| Supplier messages | Requests and answers stored on the case |
| Responses | Every SAP response recorded on the case for resolution or retry |
ScopeThe exact interfaces, objects and fields in scope are confirmed for your SAP release and deployment during technical discovery. S/4HANA Cloud Public Edition is reviewed case by case, and some landscapes may need additional configuration.
Pilot approach
A focused pilot in your QA or sandbox system proves the agent on your own data before anything reaches production.
Review SAP edition, interfaces, authorizations and representative data.
Agree one plant, the exception types in scope, owners and supplier contacts.
Run real MRP results in shadow mode for a few weeks.
Review the four measures, then add plants, exception types and autonomy.
Frequently asked questions
Security & compliance
ISO 27001:2013 certified, SOC 2 Type 2 compliant, GDPR and HIPAA ready. Every agent action is logged and auditable, and SAP credentials stay in the platform's integration accounts.
See it working
See an MRP exception go from diagnosis through supplier confirmation to an approved change, using sample data.
Request demoScope a pilot on one plant and one MRP controller in your SAP QA or sandbox system, with the four measures agreed up front.
Discuss an SAP pilot
