What Is Semantic Intelligence?

A Focus on Meaning

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February 25th

1 PM ET

Online Webinar

What You’ll Learn

  • Why structured data alone cannot support AI agents and models
  • How metadata creates shared understanding across teams and systems
  • How semantic graphs connect business meaning to data
  • Why AI success depends on embedding context and trust into the data layer

AI doesn’t just need data - it needs meaning.

Eric Kavanagh

CEO

The Bloor Group

Malcolm Chisholm

President

Data Millennium

For decades, the data industry focused on structure - schemas, pipelines, catalogs, and governance. That worked when humans supplied the missing context.


AI changes the equation.


When models and agents consume data directly, ambiguity becomes a failure mode. The “why” behind the data - business intent, context, and trust - rarely lives inside tables or APIs. Without shared understanding, even well-managed data can produce unreliable outcomes.


Semantic Intelligence addresses this gap by capturing meaning across systems. Business concepts, relationships, and intent are encoded so both humans and machines can reason over the same information.

Suresh Srinivas

CEO

Collate

Why Structure Alone Doesn’t Work in the Age of AI