Insider Brief
- ORCA Computing and SiC Systems are integrating hybrid quantum-classical computing into agentic AI systems for industrial manufacturing workflows.
- The collaboration focuses on improving AI-driven simulation, optimization, monitoring, and autonomous decision-making in chemical and biomanufacturing environments.
- The companies aim to enhance physics-informed AI models with quantum-generated data to improve accuracy, efficiency, and real-time operational control.
ORCA Computing, a leading quantum computing company, and SiC Systems, a leader in physics-informed multi-agent AI for industrial process systems, today announced a strategic partnership to apply hybrid quantum–classical computing to industrial agentic AI for chemical and biomanufacturing process design, control and maintenance. This collaboration represents the first-time quantum computing is being integrated into industrial agentic AI systems for real-world process design and operation.
The collaboration combines ORCA’s quantum computing capabilities with SiC’s AI-driven physics-informed platform to enhance modeling, optimization, and continuous operation of complex chemical and biological systems across global manufacturing environments.
As companies increasingly prioritize efficiency and scalability in manufacturing, the ability to accurately model, design and continuously optimize complex processes is critical. Traditional EPC (Engineering, Procurement, Construction), an industry with 1 trillion dollars of projected plant design and construction over the next decade, often involves extensive iterative modeling, multi-scale simulations and optimization loops that can delay project timelines and limit responsiveness during live operations.
The integration of ORCA Computing’s photonic quantum processors with SiC Systems’ SiC Suite and their model-based agentic ‘hives’ platform creates a hybrid quantum–classical high-performance computing framework powered by autonomous agentic AI workflows.
Building on SiC’s existing GPU-driven capabilities, the solution enhances process design, simulation, and optimization while also supporting continuous monitoring and adaptive control during operations. By combining quantum-generated data with classical AI models, the approach improves how complex chemical and biological systems are modeled—enhancing decision quality, enabling real-time responsiveness, and delivering measurable performance gains.
“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 CEO of SiC Systems.
In a typical new chemical or biological plant design project, SiC Suite has demonstrated the capability to save over 20,000 hours of engineering time. By automating repetitive tasks, enhancing physics-informed simulations, and orchestrating intelligent agent-driven decision-making, the platform reduces design cycles, mitigates scale-up uncertainties, and improves overall process robustness. These are factors that are particularly vital for establishing competitive new facilities.
“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 at 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.”
This partnership builds upon the award-winning technology developed by ORCA Computing and SiC Systems in collaboration with the Technical University of Denmark (DTU) and Novo Nordisk. The initiative received the 2025 HPC Innovation Excellence Award from Hyperion Research, underscoring its potential to deliver substantial engineering, scientific, and economic impact in industrial applications as the first instance of a quantum computing solution being given this award.
“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.
By enabling faster and more accurate engineering design, the combined solution supports both accelerated facility development and improved ongoing operational performance, enabling organizations to reduce time-to-market, improve efficiency, and scale complex manufacturing processes globally.
