Where AI Helps — and Where Config Wins 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
- BI AI-assisted design
- AI Wizard for iDataView
- AI management quotas
- Suggested transaction shortcuts
- Table/field recommendations
- Human-in-the-loop Test gate
Recommended workflow
- Enable monitoring alerts and review dashboard KPIs for the first production cycle.
- Open the relevant cockpit (iDataView Explorer, SQL Project, API Service Detail, or AccessGuard).
- Configure source objects, fields, mappings, or rules using session language and customer/system context.
- Run Test (iDataView Test, SQL First Row, API Test Service, or AG scan) before scheduling or publishing.
Real-world scenario (2023)
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.
Innovation here means business sees results faster — IT keeps control because every step is configured, tested, and monitored.