Industrial AI that turns scattered
field data into grounded decisions

Industrial AI collects, integrates and analyzes equipment, process and sensor data from industrial sites in manufacturing, energy and process plants to support decisions and actions. Unlike a general chatbot, it bases its answers on real field data and domain context.

Manufacturing AI is industrial AI applied to production, quality and equipment operations. Common uses include predictive maintenance that anticipates failures, quality prediction that catches defects early, and energy optimization that cuts energy use.

AI in the manufacturing industry means applying artificial intelligence to production, quality, equipment and energy operations to support prediction and automation; it is another term for manufacturing AI. The core is integrating scattered field data so that decisions have evidence behind them.

Smart factory AI brings a plant’s equipment, process, quality and energy data together in one place so the factory can sense, predict and optimize on its own. It goes beyond simple automation: it reasons from data and proposes the next action.

Energy AI is industrial AI that analyzes power and energy data to manage consumption, quality and efficiency. Combined with an energy management system (EMS), it detects peaks and anomalies and finds opportunities to save.

An industrial AI agent is a conversational AI that answers questions with sources, reasons about causes, and proposes the next action. Refinery does this by weaving scattered data into an ontology that gives it meaning.

An industrial AI OS ties equipment, systems and documents in the field into one model (an ontology), and lets apps and AI agents run on it with the same data and permissions. Instead of bolting on separate AI features, it provides connection, model, apps and agents as one system. Refinery is an industrial AI OS built this way.

First, data scattered across SCADA, MES, ERP, sensors and documents has to be brought together. Refinery sits on top of existing systems as an integrated intelligence layer, or builds from scratch where no system exists, giving data meaning so AI can reason with evidence.

Refinery weaves scattered SCADA, MES, ERP, sensor and document data into an ontology to produce grounded decisions. It sits on top of existing systems or builds new ones, and supports on-premises deployment so data does not leave your network. It is proven over 30 years across more than 100 industrial sites.