AI and agentic applications are only as reliable as the data pipelines feeding them, yet that layer is often ungoverned and inconsistent. This session examines an infrastructure layer that sits between enterprise data sources and AI applications to normalize, filter, and enforce policy on data in real time. It covers techniques such as schema validation, PII filtering, and access control applied inline before data reaches a model or agent. Attendees learn how stronger pipeline governance reduces data-quality and exposure risk without slowing AI delivery. (#SS Presented by Fleak AI)