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technologyMay 13, 202658:41pending

50 - Why Factory AI Fails Without a Data Foundation with Alexander Kruger

About this episode

Most industrial AI projects fail before they produce anything useful. The models are ready, the dashboards look great, and the executive presentation landed. But on the shop floor, nobody can get clean data out of the PLC without calling the vendor. The missing piece is a data foundation.

Alexander Kruger, co-founder and CEO of United Manufacturing Hub (UMH), joins Phil Seboa and Ed Fuentes on this episode, powered by PLCnext Technology, to explain why factory AI stalls without the right infrastructure underneath it, why boring technology beats shiny platforms, and how open source tooling is putting data ownership back in the hands of the people who run factories.

Key topics in this episode:

  • Why most factory AI projects fail at the data layer before they reach the model layer
  • How UMH went from systems integration with McKinsey to building open source data infrastructure
  • The five-step process for connecting machines, modeling data, and serving it to applications
  • Why Kafka and Postgres beat purpose-built IoT platforms for long-term reliability
  • How containers and Kubernetes solve high availability problems OT has wrestled with for years
  • The open source bet on forerunner power users who change organizations from within

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50 - Why Factory AI Fails Without a Data Foundation with Alexander Kruger

Unplugged: An IIoT Podcast

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