Physics-informed AI to
Accelerate Autonomous
Industrial Operations

Accelerating the Path to Industrial Autonomy

AI trained solely on data demands high costs, extended timelines, and many resources, delaying ROI for years.

Physics-based simulations can be predictive but are computationally intense and require deep domain expertise, limiting their use for real-time operational decisions.
Geminus leads in physics-informed AI, combining simulation with deep learning for real-time decisions, achieving ROI in weeks.

Autonomous Systems

Self-optimizing and self healing capabilities maximize productivity and minimize emissions

Model Predictive Control

Evergreen, purpose-built Al models enabling wide-spread automation

Dynamic System Digital Twins

Fully explorable Al models with instant what-if scenarios and control recommendations
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CEO Greg Fallon discusses how combining physics and AI can accelerate the energy transition.
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Founder and Chief Scientist Karthik Durasaimy speaks with Bloomberg at the World Economic Forum in Davos about the future of AI.

Learn Your Physics

Geminus models use your system’s physics for training, enabling far better predictions than models using only process data.

Accelerate ROI

Geminus is the first to bring to market breakthrough advancements in machine learning and sparse data techniques that compress time to value for AI from months – often years – to weeks

Explain Why

Our models rely on first principles training sources and feature uncertainty quantification, providing explainable and trustworthy recommendations

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