Unplanned downtime and the unique challenges of legacy "brownfield" environments hinder AI adoption compared to other industries.
The Aidu ecosystem connects operational technology, machine data, and human expertise without requiring a complete infrastructure replacement.
An industrial edge gateway with containerized protocol adapters abstracts physical connections and translates raw telemetry into a unified namespace (UNS).
A Model Context Protocol (MCP) and closed-loop agentic workflow ground the AI in verified data to prevent hallucinations and provide safe, step-by-step guidance.
Multimodal interfaces combining voice, vision, and machine data provide an intuitive user experience for operators working in noisy, hands-on environments.
The ultimate goal of industrial AI is not to replace people but to augment their expertise by providing the right context to make better operational decisions.
Jobs that call for the skills explored in this talk.