RAG to Robotics: Driving value alongside AI progress

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Artificial intelligence is advancing from simple Retrieval-Augmented Generation to agentic reasoning, real-time control, and ultimately embodied robotics. The value of each stage begins with data infrastructure: an open lakehouse that captures every sensor event, governs it at scale, and serves it to low-latency inference engines. Early investment in this backbone, including Kafka for event flow, Flink or Spark for stream ELT, and Iceberg for mutable yet audit-safe tables, creates the substrate that later unlocks productivity gains from edge sensors, smart actuators, and autonomous robots. Postponing the data layer slows every downstream upgrade, while phasing in physical infrastructure on top of a mature lakehouse lets manufacturers convert AI from a reactive aid into a self-optimizing source of profit.

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