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Your Data Agents Need ContextThe Context on Context

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Context Problem Beyond Text-to-SQLContext Layer vs. Semantic LayerMarket DirectionLooking Forward
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Read the thesis

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Your data agents need context.

This site is now centered on a simple infrastructure thesis: enterprise agents are only as good as the business context, system context, and decision context they can reliably access.

Understand the shift

Why the modern data stack set the stage for agent adoption, and why the first wave of deployments still hit a wall.

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Go beyond text-to-SQL

See why better model performance alone does not solve enterprise data reasoning without business definitions and source-of-truth context.

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See the context layer

Explore what a modern context layer needs to include beyond semantic models: entities, governance, tribal knowledge, and live update flows.

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Read the market map

A quick framing of where data gravity platforms, AI analyst tools, and dedicated context-layer companies are heading.

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