Why Did the Agent Do That? — Webinar

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WHAT YOU’LL LEARN

Stop waiting for governance. Start deploying agents that can defend themselves. Most financial institutions think the blocker is the model. It isn't. It's that the data the agents reason over lacks governed definitions, enforced constraints, and traceable lineage. BCBS 239 calls for a single authoritative source for every risk data concept. This session shows you how to build one.

Why Your Agentic AI Can't Pass Model Risk Review

The problem isn't the model. It's that "creditworthiness," "exposure," and "reportable transaction" mean different things across different systems and the agent has no way to know which one is right.

How a Semantic Layer Becomes Your Compliance Backbone

See how leading financial institutions convert existing ontologies and reference data into a governed, machine-readable foundation that both agents and examiners can rely on.

How Governed Constraints Make Bad Agent Behavior Structurally Impossible

Stop monitoring for non-conformance after the fact. Use SHACL constraints at the data layer to ensure agents can only reason over valid, policy-compliant inputs.

Lineage Is the Answer to "Why Did the Agent Do That?"

Examinable AI starts with traceable provenance. Understand how to reconstruct every agent decision, from output back to governed source, in terms reviewers will accept.

SPEAKERS

Deep expertise. Straight answers.

No generic frameworks. Our speakers bring decades of experience building semantic data infrastructure inside regulated industries and will share what actually works in production.

Nimit Mehta

CEO, TopQuadrant

Nimit provides executive leadership to the team delivering TopQuadrant's AI-ready data foundation. His hands-on approach with customers at the world's most complex enterprises helps enterprises transform data, policies, and knowledge into context that machines can reason over and humans can trust.

Steve Hedden

Product Lead, TopQuadrant

Steve leads product strategy and technical value for TopQuadrant's AI-ready data foundation, helping organizations apply semantic context and knowledge graphs to AI. His experience building ontology-backed systems at enterprise scale, combined with his leadership at the W3C, helps customers create interoperable, future-ready data and AI architectures.

Robyn Dixon

Financial Services Account Lead, TopQuadrant

Robyn guides financial services customers in transforming fragmented data into governed, AI-ready knowledge, aligning data strategy with regulatory demands and moving from static governance to dynamic, semantic infrastructure. Robyn brings direct experience across the knowledge graph and data catalog landscape.

AGENDA

60 minutes. No filler.

Every minute is designed to give you something you can act on. We skip the slides-for-the-sake-of-slides and get straight into the substance.