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Factory Data Assistant

Factory Data Assistant (FDA) is an on-premise industrial data, analytics, and AI platform designed to help manufacturers turn fragmented factory data into operational intelligence. FDA runs locally on an AI-capable industrial PC, connecting data from machines, PLCs, production systems, databases, and other factory sources and bringing it together into a common operational context.

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Horizontal strip graphic titled 'From Raw Data to Actionable Intelligence' with five blue icons and labels (Connect, Contextualize, Analyze, Apply) and four benefit callouts below

FDA provides the foundation to collect and organize manufacturing data, monitor production performance, explore historical information, and analyze downtime, scrap, quality, cycle time, and other production losses. This helps manufacturing teams move beyond simply collecting and visualizing data toward understanding where performance is being lost and where improvement efforts should be focused.

FDA is also designed as a versatile application platform rather than a fixed set of dashboards. Tailored analytics, visualizations, and intelligent applications can be quickly added to address the specific needs of a factory, production line, process, or use case—while building on the same underlying manufacturing data and infrastructure.

With local AI-capable compute, FDA provides a foundation for progressively more advanced industrial intelligence at the edge. Over time, these capabilities can move from observing what happened, to understanding why performance changed, and ultimately toward helping manufacturers identify and act on high-value opportunities for improvement. Designed for the factory floor, FDA keeps critical operational data and processing close to manufacturing operations while providing secure, browser-based access to data, analytics, and applications.

See Factory Data Assistant in Action

See how FDA can connect your factory data and provide a foundation for analytics, tailored applications, and operational intelligence.

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