Petar Zoric

Enterprise execution relies on trusted data, yet enrichment vendors often conflict and hierarchies drift. Manual validation is slow, and blind automation poses risks. This session details a production-grade validation system built on Databricks to transform CRM chaos into governed data layer. Using Delta Sharing feeds from various providers, we built a triangulation framework to reconcile signals across parent hierarchies, Salesforce structures, and revenue estimates. Rather than accepting data blindly, we implemented an AI governance layer that: 1. Reasons across enrichment signals to propose re-parenting. 2. Validates outputs via secondary agents to eliminate hallucinations. 3. Automates approvals based on confidence thresholds or escalates for human review. Attendees will learn to design multi-agent architectures and AI guardrails that preserve trust while accelerating planning cycles—enabling autonomous, governed workflows that improve revenue visibility at scale.