SiC & ORCA join on quantum industrial AI partnership
Fri, 8th May 2026 (Yesterday)
SiC Systems and ORCA Computing have formed a strategic partnership to apply hybrid quantum-classical computing to industrial agentic AI for chemical and biomanufacturing design, control and maintenance. They describe it as the first integration of quantum computing into industrial agentic AI systems for real-world process design and operation.
The agreement combines ORCA's photonic quantum processors with SiC's physics-informed AI platform, SiC Suite, including its model-based agentic "hives" system. The aim is to improve modelling, optimisation and the continuous operation of complex chemical and biological manufacturing processes.
The partnership targets an area where design work is often lengthy and iterative. Engineering, procurement and construction projects for new plants typically rely on repeated modelling, multi-scale simulation and optimisation, extending timelines and making it harder to respond quickly once facilities are operating.
SiC said its software has already cut more than 20,000 hours of engineering time from a typical new chemical or biological plant design project. It attributed those savings to automating repetitive work, improving physics-based simulation and using agent-led decision systems to manage design choices.
ORCA will add quantum computing to that process. The hybrid setup is designed to use quantum-generated data alongside classical AI models to improve how chemical and biological systems are represented, with the goal of strengthening design decisions and operational responses in live industrial environments.
Industrial focus
The companies are positioning the work around practical manufacturing use rather than laboratory research. Their focus includes process design, monitoring, adaptive control and maintenance in chemical and biomanufacturing facilities, where operators must balance efficiency, reliability and scale.
That emphasis reflects broader pressure on manufacturers to shorten development cycles while managing increasingly complex production systems. In chemicals and biomanufacturing, delays in design or scale-up can directly affect project costs and the timing of new capacity.
According to the companies, the project also builds on earlier work with the Technical University of Denmark and Novo Nordisk. That initiative received the 2025 HPC Innovation Excellence Award from Hyperion Research, which they described as the first time a quantum computing solution had won the award.
The companies provided few technical details on commercial deployment, but said the combined system is intended to support both early facility design and later plant operations. That includes improving process robustness and addressing uncertainties that can emerge when laboratory or pilot systems are scaled to full production.
For SiC, the tie-up extends the use of agentic AI in industrial software by adding quantum computing to selected modelling and optimisation tasks. For ORCA, it offers a way to place quantum systems inside a workflow tied to specific industrial outcomes rather than stand-alone computing experiments.
Dr Christopher Savoie outlined the rationale for the agreement.
"This collaboration shows how optimization can become both autonomous and explainable. By integrating quantum-accelerated computing with our agentic AI platform, we are empowering engineering teams to accelerate the design of new chemical and biological plants-adding to already proven savings of over 20,000 hours in a typical project while delivering higher accuracy and resilience. This capability is essential for modern manufacturing programs globally," said Dr Christopher Savoie, co-founder and chief executive officer of SiC Systems.
Quantum role
ORCA said the partnership could change how complex industrial systems are simulated. It argued that some interactions in chemical and biological environments are difficult to model with classical systems alone, especially when many variables change at once during live operations.
Per Nyberg described the expected effect on industrial modelling.
"When combined with SiC Suite's multi-agent AI, ORCA's hybrid quantum-classical approach enables a fundamentally different way to model and optimize complex chemical and biological systems," said Per Nyberg, chief commercial officer of ORCA Computing.
"By applying quantum computing to models grounded in real-world systems, we can capture complex interactions that are difficult to simulate classically, improving the fidelity of both design and operational decision-making in dynamic industrial environments," he said.
SiC's scientific leadership also framed the work as part of a broader effort to change how industrial processing is engineered.
"This work demonstrates how agentic AI can transform industrial processing. Our physics-informed platform, enhanced by quantum acceleration, addresses the multi-scale complexities of plant design, delivering substantial engineering time savings and enabling the rapid deployment of safe, efficient, domestic production facilities," said Dr Seyed Soheil Mansouri, co-founder and chief scientist of SiC Systems.