QuantWare has reduced quantum processor bring-up time from days to under three hours per feedline with Boulder Opal, a new autonomous calibration system, the company says. The automation also achieves 99.95% median 1-qubit gate fidelity across an entire device, a key metric for reliable quantum computation. “By encoding physics-informed AI into an autocalibration framework, Boulder Opal is a repeatable, deterministic, and scalable solution for quantum control,” says Q-CTRL, whose technology underpins the system. Boulder Opal is immediately compatible with Quantum Machines and Qblox controllers, streamlining deployment for existing quantum computing setups.
QuantWare Device Bring-Up Under 3 Hours with Boulder Opal
QuantWare’s Boulder Opal achieves sub-three-hour device bring-up times per feedline by automating calibration routines previously requiring days of manual operation, a shift enabled by physics-informed artificial intelligence. The system extracts live and historical device data, presenting parameters and plots in an interactive visualization intended to maximize quantum processing unit use and streamline performance analysis. This level of automation frees technical teams from repetitive control operations, allowing them to concentrate on more complex tasks within quantum computing development.
QuantWare describes the core of Boulder Opal as a repeatable, deterministic and scalable application of AI to the traditionally painstaking process of quantum device calibration, according to the company. Achieving 99.95% median 1-qubit gate fidelity is a key benefit of this automated approach, which not only reduces calibration time but also aims to provide consistent, predictable results, minimizing variability between devices and over time.
QuantWare, founded in 2021 as a spinout from TU Delft/QuTech, has quickly established itself as a commercial manufacturer of off-the-shelf superconducting quantum processors, offering systems ranging from 5 to 64 qubits. The company’s $178 million funding round in May 2026 highlights growing investor confidence in its approach to scaling quantum hardware, with the funds earmarked for increased production of industrial quantum processors. This investment follows the November 2025 launch of the Quantum Utility Block, a pre-integrated system developed in collaboration, further solidifying QuantWare’s position within the emerging quantum ecosystem.
This interoperability is a deliberate strategy, evidenced by QuantWare’s participation in the Quantum Utility Block, a pre-validated reference architecture combining QuantWare processors, control electronics and software. The company’s foundry services, introduced in February 2026, also aim to lower barriers to entry for quantum hardware development by providing access to fabrication resources and expertise.
Leads the market in adapting AI technology into real, impactful capabilities for quantum computing. This approach aims to move beyond simple automation toward intelligent autonomy, enabling reliable execution and a frictionless quantum bring-up process. QuantWare’s KiloFab, announced in May 2026, is designed to build 40,000-signal line quantum processors, a step that highlights the company’s commitment to scaling production capacity.
This expansion is coupled with a silicon-based VIO architecture introduced in June 2026, intended to facilitate the development of systems with 10,000 qubits or more. The company reported on September 25, 2026, that scaling quantum power depends on efficiency, not just qubits. The system’s ability to extract and visualize historical device data provides a comprehensive view of performance trends, enabling proactive maintenance and optimization.
The company, with approximately 58 employees, is actively working to streamline the quantum workflow, and Boulder Opal represents a step toward that goal, the company says. The system’s autonomous routines cover feedline and qubit discovery, coupler characterization and gate calibrations, automating tasks that previously required significant manual effort and expertise, QuantWare reports.
This automation not only accelerates the bring-up process but also reduces the potential for human error, leading to more consistent and reliable results. The ability to run these routines autonomously is intended to maximize uptime and optimize the overall performance of QuantWare’s quantum processors.
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