Who We Are
We believe manufacturing should not merely follow instructions—it should observe, learn, and improve itself. Our work merges automation, machine intelligence, and process science to create systems that are self-optimizing, sustainable, and deeply human-centered in their design.
Our Mission
To engineer the transition from conventional process control to autonomous, self-learning manufacturing ecosystems—starting with the biorefinery as our pilot usecase. We turn complex industrial processes into intelligent networks capable of continuous adaptation and sustainable performance.
Our Approach
Our approach blends digital personas of a process, sensor-rich control frameworks, and data-driven learning loops.
Each system we build is designed to observe, infer, and act—linking the physical and digital worlds through real-time feedback. This creates an evolving production environment where automation doesn’t just execute—it thinks.
Our engineering teams work at the intersection of AI, process modeling, and control systems, transforming how materials, energy, and information flow through industry.
