The AI Data Gap: Why a Semantic Layer is the Missing Link to Production-Ready AI

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    Feb 19, 2026 @ 12pm-1pm ET
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    Webinar

What It's About

The bridge between raw enterprise data and a successful AI application is often missing a critical component: context. While most organizations are rushing to implement Large Language Models (LLMs), they are finding that their data is too fragmented, siloed, and "messy" for AI to be useful. This is the AI Data Readiness Gap. Traditional data pipelines focus on moving data, but they fail to capture the meaning and relationships behind it.

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What You'll Learn

In this session, we dive into why a Semantic Layer is the essential architectural foundation for production-ready AI. We will demonstrate how Stardog’s Enterprise Knowledge Graph moves beyond simple keyword searches to provide a machine-understandable map of your entire business. Discover how to stop the endless cycle of data cleaning and start delivering AI that is grounded in business logic, fully traceable, and ready for the enterprise.

In this session, you will learn:

  • The Blueprint for AI Data Readiness: Understand the shift from traditional ETL to a "Zero-Copy" semantic approach that makes your data immediately accessible to AI without the need for massive data movement.
  • Bridging the Context Gap: Learn how to use ontologies to map disparate data silos into a unified Knowledge Graph that provides the "ground truth" for AI models.
  • Achieving Explainable AI: Discover how a Semantic Layer provides a clear lineage and logical path from an AI's output back to its source, ensuring your AI initiatives are governed, compliant, and trustworthy.