Enterprise: ERP, CRM and SAP · Enterprise scenario · Proposed architecture
Recovering CRM and ERP sync errors (Integration Control Tower)
Every event between systems passes identifier, version and duplicate control, is validated and is written to the target system once. Timeouts, temporary errors and data errors are handled on separate paths, unresolved events go to an error queue, and at the end the two systems are reconciled.
Who it is for: Companies with many integrations, IT and business operations teams
Systems: CRM, SAP S/4HANA (sales processes), Integration platform, Monitoring and ticketing system
Problem
Events between the CRM and ERP sometimes get lost, sometimes arrive twice and sometimes stop halfway. Errors surface only when a customer complains, nobody knows who should fix them, and resending creates duplicate orders.
How it works today
Integration errors stay in log files. When an IT employee spots an error, they look for the cause by hand and resend the message without checking whether the document was already created in the ERP. The business side gets the fix task by email, and differences between the two systems show up in the month-end comparison.
What this scenario changes
Every event is received with an ID and payload version, duplicates are checked in the event log, and schema, identifier and business rule checks run in parallel. The ERP write uses an operation ID: on a timeout the ERP is searched first, on a temporary error there is a limited delayed retry, and a data error goes to the responsible person as a fix task. An unresolved event lands in the operator's error queue, after the fix it is reprocessed from the selected step, and a reconciliation job compares the two systems.
The integration method is chosen based on the SAP version and the available interfaces.
Process stages
- Event intake: Receive the event with its ID and payload version. Result: Received event with a recognized version
- Duplicate control: Prevent the same event from being processed twice. Result: A new event goes to processing, a repeat event is only logged
- Data checks: Check schema, identifiers and business rules in parallel. Result: Combined result of the three checks
- Error analysis and fix: Find the cause of the data error and fix it at the source. Result: Approved fix and safe reprocessing. Approval: Business data owner
- Operation in the ERP: Create the order in the ERP exactly once. Result: Sales Order, or the event in the error queue
- Updating the other system: Update the CRM record with the ERP result. Result: Order number and status in the CRM
- Reconciliation: Compare the actual state of the two systems. Result: Match confirmed, or a difference task for the operator
Participants
- CRM
- Integration platform
- ERP / SAP
- Monitoring and ticketing
- Business data owner
- Integration operator
The role of AI
Summarizes error logs, finds similar earlier events and suggests a fix. It does not apply the suggestion automatically: the responsible person accepts and carries out the fix.
Rule-based automation
Event ID, version, duplicates, schema, identifiers and business rules are checked automatically. ERP and CRM writes are idempotent with an operation ID. After a timeout the operation is looked up in the target system first, temporary errors are retried a limited number of times with a delay, and data errors are not resent. The duplicate check alone does not guarantee "exactly once" across all systems, which is why the reconciliation job is kept.
Human approval and exceptions
For a data error, the business data owner accepts or rejects the AI suggestion and makes the fix at the source. When the retry limit is reached, the integration operator sees the cause and related documents in the error queue and resumes processing after recovery. The operator investigates any difference found in reconciliation.
Frequently asked questions
Do you have a ready-made SAP integration?
This page shows a proposed architecture and a synthetic demo. The integration method is chosen in the project based on the SAP version, active modules and available interfaces.
Does duplicate checking mean "exactly once"?
No. Checking by event ID prevents the same event from being processed twice, but it does not guarantee "exactly once" across all systems. That is why every write has an operation ID, the target system is checked first after a timeout, and a reconciliation job compares the actual state of the two systems.
Does AI fix the error by itself?
No. AI summarizes the logs, finds similar events and suggests a fix. The responsible person accepts the suggestion and makes the fix, and then the event is reprocessed from the selected step.