AI success is no longer just about choosing the right model. As organizations move from experimentation to agentic AI, the real differentiator is the quality, meaning, governance and context surrounding the data those systems rely on.
This webinar explores why semantics and the contextual layer are becoming critical foundations for trusted, scalable AI. We begin with a practical overview of what semantics means in the age of agentic AI and why it matters. You’ll learn how semantics creates a contextual layer that helps connect data, metadata, rules and relationships with business meaning. You’ll also learn why this matters when AI systems need to reason, retrieve, act and explain.
We are joined by Balvinder Dang, CEO and Co-Founder of Datavid, who shares real-world implementation perspectives and lessons from successful projects where semantic modeling, knowledge graphs, contextual enrichment and governed data foundations have helped organizations move beyond simple retrieval towards more accurate, explainable and business-aligned AI outcomes.
View the on-demand webinar to discover:
- Why semantics is becoming essential to agentic AI, not just data management
- How contextual layers improve retrieval, reasoning, trust and explainability
- What successful implementations look like in practice
- When to think about semantics as a foundation for scalable, governed AI
- Where to start when building AI systems that need more than raw data and model intelligence
Philip Miller
Progress Software
Balvinder Dang
Datavid
Related Resources
