SAP AI Agent · SCM · APO · CIF · CCR Configurable
Design scenario · how the agent is configured to work
Why it matters
Failed queues and CCR inconsistencies mean APO doesn't see orders, stock or master data that ECC has. Planners often don't notice until a plan is wrong.
How it works
The same four steps as every Artificio agent. The agent does the research and the paperwork; your teams make the decisions.
Failed CIF queues and the results of your CCR runs.
Groups hundreds of errors into the few causes behind them.
Proposes the fix for each cause and the re-transfer that follows.
Re-transfers after approval and checks the next CCR run.
Worked example
After a weekend master data change, 214 CIF entries fail overnight. Here is what the agent finds before the planners start their day.
12 materials changed on Sunday are not in the active integration model, so their orders can't transfer to APO.
| Cause | Entries | Proposed fix |
|---|---|---|
| Materials not in active model | 198 | Regenerate and activate the model for plant 1000 |
| Missing location products | 11 | Create location products in APO for 3 materials |
| Lock errors | 5 | Reprocess after the nightly job finishes |
| CCR: orders missing in APO | 61 | Re-transfer after the model is active |
| Duplicates | None | No affected order exists in APO yet |
Orders are re-transferred only after the integration model is active, and the next CCR run confirms nothing is missing.
Design scenario · 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 D. Brooks (SCM lead) to approve regenerating the integration model for plant 1000, asked Mon 2 Nov at 05:12.
After the model is active, the planner approves the re-transfer. The next CCR run checks the result.
| Step | Owner | Status |
|---|---|---|
| Diagnosis and grouping | Agent | Done |
| Integration model | D. Brooks · SCM lead | Waiting |
| Location products | Master data | Waiting |
| Re-transfer and CCR check | Planner | On hold |
Regenerate and activate the integration model for plant 1000 to include the 12 materials changed on Sunday? 198 failed CIF entries depend on it.
Illustration of how this agent's cases appear on the Artificio platform · names and values are fictional
Capabilities
Failed transfers found, grouped and corrected before they reach the plan.
Ownership
You map causes and objects to teams. Whoever answers first decides, and anything unassigned goes to the SCM 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 reprocessing lock errors after the conflicting job has finished, 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.
| CIF queues | Failed inbound and outbound CIF entries |
|---|---|
| CCR results | Inconsistencies by object type |
| ECC objects | Orders, stock and master data |
| APO objects | Location products and transferred orders |
| Re-transfer | Approved re-transfers of objects |
|---|---|
| Integration models | Changed by the SCM team, with approval |
| Alerts | Diagnoses sent to the owning team |
| Responses | Every SAP response recorded on the case |
ScopeScoped to SAP ECC with SAP APO. Embedded PP/DS in S/4HANA has different integration considerations and is evaluated separately. The queues, objects and corrections in scope are confirmed for your landscape in technical discovery.
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 the plant, the CIF objects in scope, the owners and approvals.
Watch real CIF queues and CCR runs in shadow mode.
Review the four measures, then add plants, objects and approved automatic fixes.
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
Talk through your CIF monitoring and APO integration with our team, and see how a similar agent works on the Artificio platform.
Request DemoScope a pilot on one plant or planning area in your SAP QA or sandbox system, with the four measures agreed up front.
Discuss an SAP pilot
