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.

Fire Opal

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.

Up to 9,000X algorithmic enhancement on cloud quantum computers
Q-CTRL improvements comparision

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 on cloud hardware. They achieve better algorithmic success and faster execution, all without needing to worry about the hardware

Fire Opal workflow

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 tools so you can focus on building the future, not fixing the hardware.

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Enabeling future quantum computing applications: high value financial models; next-generation machine learning; clean energy materials discovery; pharmaceutical drug discovery; efficient logistics optimization

Real-world use cases

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Make quantum technology useful

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Berkeley Lab
Imperial College London
Northwestern University
USC Viterbi School of Engineering