Context

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A semantic layer is a governed catalog of definitions that sits on top of your existing data and tells agents and people what to trust. Here's how we built one into PostHog's context warehouse.

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RAG fixes what the model reads before it sees the question. Jev fixes what the model can answer before it sees the state. They're the same design, applied to opposite ends of the model.

Most enterprises have plenty of automation and not much transformation. The pilots worked. The bots run. The productivity curve flattened anyway. It is the most repeated story in the enterprise, and the next wave, Agenti...

The organizations pulling ahead in AI right now built a trusted, connected view of their data first.

If we ignore the context, we shouldn't be surprised when AI models or systems show poor performance or behave unpredictably.