Autonomous materialization is useful when it is tied to workload evidence, governance checks, and lifecycle management.
AI agents need more than metric names. They need composable business logic that survives multi-step analysis.
Dremio Agentic Lakehouse is easiest to understand as two ideas: data built for agent access and platform work managed by agents.
Low-latency analytical systems can help active agents, but only when event loops include validation, context, and safety boundaries.
