Our users

Quantum computing developers

Power development teams with quantum control tools. The quantum computing revolution is here – we have built the tools to make it practical.

Solutions for quantum development and software engineering teams

Improve algorithmic speed and performance

Realizing useful computations on quantum computers requires overcoming the true bottleneck in the field: instability and error. Hardware error remains the roadblock on the path to achieving true quantum advantage - including users of cloud quantum computers.

Quantum computers are not like conventional machines. Conventional computers can run for almost a billion years without suffering a hardware fault, but qubits in quantum computers can fail in less than a second.

Our users leverage our quantum control infrastructure software to build and deploy real-world quantum applications by simple, seamless, and automated integration of error suppression in their quantum workflows.

Solutions for algorithm researchers

Streamline quantum workflows

Teams with full exposure to the inner workings of quantum computing hardware have had an unfair advantage. We are changing that for our users.

Quantum algorithm researchers seamlessly pass algorithms through our tools and then execute them on cloud hardware. They achieve better algorithmic success and faster execution, all without needing to worry about the hardware.

We enable you to develop and execute error-robust quantum applications for quantum computers now and in the future, enabling scalable development. AI engines autonomously optimize quantum algorithms at the gate and circuit level to deliver the maximum performance achievable in hardware.

Make quantum computing practical with simple Python developer tools so you can focus on building the future, not fixing the hardware.

Real-world use cases

Nord Quantique

Nord Quantique is accelerating the path to useful quantum error correction with Boulder Opal

Nord Quantique used Boulder Opal to design a hardware-efficient QEC protocol for a superconducting system where quantum information is encoded in GKP states.


increase in logical qubit lifetime

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Given the complexity of the physics at play, being able to perform closed-loop optimization of a few physically motivated parameters of the quantum error correction protocol with Boulder Opal is very valuable to us.

Dany Lachance-Quirion
VP of Quantum Hardware
Nord Quantique
Australian Army

Improving Army logistics with quantum computing

With Fire Opal, the Australian Army tested and validated a quantum computing solution on real hardware that promises to outperform their existing methods.


improvement in the likelihood of finding an optimal solution with Fire Opal over the default hardware execution

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Optimally routing 120 convoys can take more than a month of classical computation. The Australian Army is evaluating the potential of quantum computing to provide improvements; however, it’s been difficult to validate the feasibility of a quantum solution due to hardware noise. With Fire Opal, an algorithmic enhancement software, we are able to achieve results on quantum computers that build confidence in our quantum roadmap.

Marcus Doherty
Australian Reserve Officer
Australian Army
Blue Qubit

Enabling data loading for quantum machine learning with Fire Opal

BlueQubit demonstrated groundbreaking loading of complex distribution information onto 20 qubits for a QML application by using our error suppression product.


Better performance in terms of Total Variational Distance (TVD), which measures the deviation from perfect data loading.

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As we develop novel techniques to solve some of the quantum industry’s hardest challenges, Fire Opal is an essential tool to reduce the impact of hardware noise and demonstrate successful results with deeper and wider circuits.

Hayk Tepanyan
Chief Technology Officer
Blue Qubit
Q-CTRL Partner

Reducing quantum compute costs 2,500X with Fire Opal

With Fire Opal a financial company was able to run algorithms on more cost-effective hardware systems while achieving results comparable to more premium systems


Reduction of quantum compute cost

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We wanted to challenge Fire Opal’s capabilities by running a quite complex, unoptimized circuit. The results were extremely promising. The only comparable results we’ve seen have come from hardware that is currently too expensive to run extensive tests on.

Dr. Valtteri Lahtinen
Chief Scientific Officer
Q-CTRL Partner

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Make quantum technology useful
Alice & BobAtom ComputingChalmers UniversityIBM QuantumImperial College LondonION QNorthwestern UniversityRigetti