AI for Custom Z*/Y* Tables — Safely addresses a problem most SAP landscapes know too well: Generic AI hype falls flat in SAP without recommendations grounded in your real tables and a human approval step before anything goes live.
AI usage is governed centrally with model and quota controls, and every recommendation respects your organization's data boundaries and session language.
Innovation here means shorter design cycles, not unreviewed code in production.
Capabilities you use in iDataEngine
- Module and join suggestions
- Human-in-the-loop Test gate
- Suggested transaction shortcuts
- AI management quotas
- Safe custom table naming checks
- Table/field recommendations
Recommended workflow
- Enable monitoring alerts and review dashboard KPIs for the first production cycle.
- Configure source objects, fields, mappings, or rules using session language and customer/system context.
- Extend the same definition to the next channel (API, SQL, MF, BI) without redesigning from scratch.
- Run Test (iDataView Test, SQL First Row, API Test Service, or AG scan) before scheduling or publishing.
Real-world scenario (2024)
BI designer uses AI layout suggestion, then publishes under auth fields — speed without bypassing role review.
Why it matters
Recommendations grounded in your real SAP tables and iDataEngine's own module knowledge beat a generic copilot guessing at table names that don't exist.
Measured on lead time, defect rate, and audit readiness, the platform pays back in the first production quarter.