Dezide

Dezide uses Bayesian networks to calculate the most efficient troubleshooting path based on probability, cost, and time. Unlike static decision trees, this engine adapts dynamically to the technician's answers, which provides accurate diagnostics even when information is incomplete. This significantly reduces the time spent identifying root causes.

The platform offers native apps for iOS and Android that allow technicians to download guides and perform full diagnostics in remote locations. This offline capability ensures that field staff working in mines or offshore turbines can access critical expert knowledge without needing an active internet connection.

This feature uses machine learning to analyze feedback and data from actual field usage. It automatically suggests improvements to probabilities and repair actions to ensure that the troubleshooting guides evolve over time. This keeps the knowledge base accurate and reflective of the real-world aging of equipment.

The Studio is a drag-and-drop authoring environment where experts can visually model causes, actions, and questions. It separates the troubleshooting logic from the content, which allows for easy management of complex hierarchies and multilingual support without requiring any coding skills from the subject matter experts.

Dezide software can connect directly to IIoT devices to automatically populate answers in the guide using real-time machine data. By reading sensor values directly from the asset, the software reduces manual entry errors and speeds up the diagnostic process to move from reactive to prescriptive maintenance.