Industrial AI: Built for reality, operation, and people

Industrial environments are complex. Machines are decades old, interfaces are proprietary, and data lives in silos across multiple manufacturers. Developers often face heterogeneous systems with no APIs, outdated protocols, and tightly coupled architectures. Greenfield approaches or full platform replacements are rarely feasible – they are slow, expensive, and risky.

Industry is often not the center of attention in AI and software discussions, yet it is a key driver of innovation and economic value. Focusing on industrial use cases is not only worthwhile, it unlocks real impact.

In this session, we show how to build and deploy AI products quickly on legacy industrial systems using a pragmatic, modular approach. By combining edge computing, MACH principles, and MCP, developers can integrate old systems incrementally, orchestrate workflows, and create measurable value from the first use case.

Using examples from the iDOO ecosystem, we demonstrate how AI agents act as a central touchpoint between humans, machines, and data. Multimodal interaction makes complex industrial processes accessible and actionable without rewriting existing infrastructure.

The session includes a demo showing the flow from raw machine data through edge services and orchestration to actionable AI output. Real integration patterns, practical insights, and solutions for industrial AI. Built for reality, operation, and people.