World Congress 2026 Europe - Virtual Stage • Jul 2, 2026 • Session details

Why Your AI Agent Keeps Hallucinating Your Data: Building Deterministic Context Layers

Tom Kaltofen , Xiaoheng Chen

Raw enterprise data guarantees AI hallucinations in production. Build a deterministic context layer to provide stable, validated interfaces that transform experimental bots into reliable enterprise tools.

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#1 about 2 min

Why AI agents hallucinate organizational data

Data model interfaces are often overlooked when scaling from simple chatbots to enterprise products.

#2 about 3 min

Differences between coding agents and organizational agents

Coding agents succeed due to structured environments and easy evaluation, unlike complex enterprise data systems.

#3 about 12 min

Understanding data infrastructure components through family metaphors

Key systems like feature stores, semantic layers, and knowledge graphs each handle specific architectural duties.

#4 about 6 min

Composable abstraction layers for deterministic AI context

Replacing rigid data pipelines with interchangeable plugins allows for scalable and reproducible context layers.

#5 about 10 min

Live demonstration of dynamic data redaction plugins

A coding agent uses composable units to dynamically redact sensitive information and track data lineage.

#6 about 4 min

Bringing software best practices to data context scaling

Stable interfaces and testing frameworks make agent contexts reproducible for reliable production deployment.

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Preparing enterprise data foundations for artificial intelligence agents

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10:17 min

Discussion on AI hallucinations and practical developer workflows

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3:01 min

How missing context leads to subtle AI agent hallucinations

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2:02 min

Redefining the software architect role for AI pipelines

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4:29 min

The impact of agentic AI on data architecture

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52 sec

Structuring data access with Fabric Data Agent

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