Empadra Twin creates a continuously updated digital model of your physical world — synchronized in real time, powered by AI that finds patterns your teams don't have time to look for.
The digital twin mirrors your physical assets continuously — updated by Vision's live feeds and historical data streams. No stale snapshots.
Twin's models learn what normal looks like for every asset — and surface patterns that predict failure weeks before it happens.
Run what-if scenarios against the live model. Understand how a planned maintenance action or a process change will affect downstream systems.
When something goes wrong, Twin traces causality through the entire connected system — identifying the real root cause, not just the symptom.
Twin continuously identifies inefficiencies, bottlenecks, and suboptimal operating conditions — surfacing recommendations to Command.
Not just statistical ML — Twin combines first-principles engineering models with data-driven AI for higher accuracy in low-data regimes.
Twin's AI models are trained on your specific equipment, your specific process conditions, and your specific failure history. Not generic models — your operation's physics, encoded.
Live demo using real equipment failure scenarios from your industry.