AI Master Data Steward for SAP SuccessFactors

• Cleaner data, less manual clean‑up
  Run checks against your selected SuccessFactors datasets and reduce repetitive “hunt & fix” admin work through structured AI suggestions and approved auto‑updates.
• Rules owned by HR — not stuck in IT backlog
  HR admins can create rules and consistency checks themselves, instead of needing developers each time you want a new data validation.

• Transparent, auditable corrections
  You get visibility on what’s wrong and what the AI proposes to change—so nothing is silently altered without review. 

• Define and run data quality rules
  Your HR admins can create data quality checks themselves: from straightforward “hard rules” (what must be true) to checks that validate relationships between fields. You can also choose which dataset each rule runs on, so you target only what’s relevant and keep checks efficient.
• Clear findings & guided fixes 
  When the solution finds an inconsistency, it shows it in a structured, actionable way, including a suggested correction. Your team can review the proposed fix and, once approved, the solution can update the SuccessFactors data automatically, reducing repetitive manual clean‑up.
• Continuous improvement through HR feedback
  As your HR admins confirm or reject suggestions, that feedback is captured as guidance for future checks. In practice, this means the solution can stop surfacing the same “acceptable exceptions” again and again, making the checks more aligned with your real‑life rules and context.
• Governance & control (privacy‑aware and scope‑controlled)
  You remain in control of what gets checked and shared: the solution supports limiting datasets per rule (to reduce unnecessary processing), and explicitly mentions masking personal data when datasets are sent for processing. This helps you operationalize AI in a way that’s more compatible with HR data governance expectations.

Price on request