Demo Day: YAML Is Undermining Your AI

Governing the meaning behind YAML-defined data products and semantic models

YAML helps teams move quickly across pipelines, models, APIs, and integrations. But by itself, YAML is not authoritative context for AI: it does not prove that definitions are approved, terminology is standards-aligned, or ownership is clear. Ask any AI running on top of YAML files to prove it is using trusted context, and it balks.

Watch this 30-minute session for a demo on how teams are using knowledge graphs and ontologies to govern the authoritative context behind YAML-defined assets, connecting them to trusted standards such as IDMP, MedDRA, ISA-95, and FIBO while improving discoverability, traceability, reuse, and AI trust.

92 data leaders registered

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WHAT YOU’LL LEARN

YAML config quietly runs your pipelines, models, and integrations, but it isn't tied to the terminology standards your industry already trusts. In 30 minutes, see how to close that gap: turning ungoverned YAML into governed, standards-aligned data products your teams, and your AI, can trust.

YAML Doesn't Make Meaning Authoritative

It can't enforce enterprise meaning, align terminology, or prove two teams mean the same thing by the same key, metric, or field.

Semantic Debt Adds Up Fast

YAML-defined assets scatter across Git, platforms, and workflows with unclear ownership, inconsistent standards alignment, and weak traceability.

Now It's an AI Trust Problem

As agents and semantic layers consume these files directly, that ambiguity becomes a governance, trust, and hallucination risk, not just a hygiene issue.

Govern the Context, Not Just the File

See YAML made discoverable, owned, standards-aligned, and traceable to IDMP, MedDRA, ISA-95, and FIBO turning scattered artifacts into governed context for data, semantic models, and AI.

SPEAKERS

30 Minutes. Live Product. Real Governance Problem.

TQ Demo Days set up real problems and showcase how experts are solving them.

Laurie Nelsen

Sr. Semantic Solutions Engineer

Laurie partners with customers to architect technical and business strategies that activate enterprise context. Drawing on her foundation in library science and information architecture, she specializes in the practical application of ontologies, taxonomies, and knowledge graphs. Previously a Sr. Ontologist at Mayo Clinic, Laurie leverages her deep experience in life sciences—a sector at the forefront of semantic data adoption—to help enterprises establish robust semantic layers and future-proof data foundations.

John Murphy

Semantic Data Governance Lead

John guides enterprise organizations on operationalizing business context at scale, transforming complex enterprise metadata, ontologies, controlled vocabularies, and reference data into governed, reusable assets. He focused on interoperability, data products, analytics, and AI strategies. John's experiences include roles at Oracle, OpenText, and the US Army.

AGENDA

30 minutes. Live product.

TQ Demo Days set up real problems and showcase how experts are solving them.