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Field notes from 50+ conversations with data teams: the five stages of agentic analytics, what breaks at each, and what teams want next.
Context is now table stakes for analytics agents. The new problem is keeping it true as the business keeps moving.
AI agents don't just need a semantic layer. They make it impossible for humans to operate without one.
AI tools are enabling business users to contribute directly to dbt models and metric definitions. The data stack isn't ready.
AI agents don't remove the human cost of making data useful. They redistribute it.
Cassis is in early access. We're working with data teams at companies with well-structured data stacks (between 200 and 1000 people) who are ready to move beyond duct-taped context.
Thanks. We'll be in touch.
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