SiC Systems and ORCA Computing have announced a strategic partnership to apply hybrid quantum–classical computing to industrial agentic AI for chemical and biomanufacturing plant design. This collaboration marks the first integration of quantum computing into autonomous “agentic” workflows—AI systems capable of independent reasoning and decision-making—for real-world engineering, procurement, and construction (EPC) projects. By combining ORCA’s photonic quantum processors with SiC Systems’ SiC Suite, the partnership aims to accelerate the design and continuous optimization of complex manufacturing facilities.

The hybrid framework leverages SiC’s physics-informed platform and its “hives” of autonomous AI agents to manage multi-scale simulations and iterative modeling loops that traditionally constrain plant design. Integrating quantum-generated data into these classical AI models enhances the simulation of complex chemical and biological interactions that are difficult to model accurately with standard GPU-driven high-performance computing. This capability is expected to improve decision quality during the design phase and enable real-time, adaptive control during live operations, reducing scale-up uncertainties and improving overall process robustness.

In typical plant design projects, the SiC Suite has demonstrated the capacity to save over 20,000 hours of engineering time by automating repetitive tasks and orchestrating intelligent decision-making. This project builds on award-winning research previously conducted with the Technical University of Denmark (DTU) and Novo Nordisk, which received the 2025 HPC Innovation Excellence Award from Hyperion Research. By reducing design cycles and mitigating the time-to-market for domestic production facilities, the partnership seeks to deliver measurable performance gains in an EPC industry projected to manage $1 trillion in plant construction over the next decade.

You can find the official announcement regarding the SiC Systems and ORCA Computing partnership here.

May 7, 2026

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