AQSolotl and QuantrolOx Partner to Automate Quantum System Calibration

AQSolotl, a specialist in quantum computing hardware and integrated solutions, has formed a strategic partnership with QuantrolOx, developer of automated machine learning-based control software for quantum technologies. The collaboration aims to accelerate the shift from experimental quantum systems to scalable, production-ready infrastructure by integrating AQSolotl’s Chronos-Q control system with QuantrolOx’s Quantum EDGE platform.

The unified stack created through this partnership is designed to reduce manual calibration and improve system stability in quantum computing. By combining high-speed control hardware with automated machine learning-driven workflows, the joint solution aims to deliver a more efficient operating environment for quantum engineers and researchers. This integration will significantly shorten tuning cycles and enable more consistent qubit performance.

One of the sector’s most persistent challenges is the reliance on manual, time-intensive system tuning. As quantum processors scale beyond early-stage prototypes, increasing qubit counts and tighter performance thresholds make manual calibration impractical. The industry is shifting towards automation and integrated control layers to improve reliability, reduce downtime, and enable continuous operation.

The partnership between AQSolotl and QuantrolOx will be executed in two phases. In the immediate term, the companies plan to deploy AQSolotl’s hardware on the QuantrolOx Quantum Testbed and integrate automated control workflows. This joint solution is expected to support emerging workloads such as quantum AI training, where repeatability and system fidelity are critical.

Vishal Chatrath, CEO and Co-Founder of QuantrolOx, emphasized that automation is becoming essential as quantum systems grow in complexity. ‘By bringing machine learning-driven control directly into AQSolotl’s hardware layer,’ he said, ‘we can enable more stable and repeatable performance with significantly less manual intervention.’

AQSolotl specializes in making advanced quantum technology accessible and practical for industry through its modular quantum control platforms and deployable quantum AI solutions. The company focuses on adaptability, cost-effectiveness, and seamless integration with classical computing to address complex computational problems in sectors such as finance, pharmaceuticals, energy, and logistics.

QuantrolOx develops automated machine learning-based control software that is technology agnostic and applicable to all types of quantum technologies. Their goal is to maximize quantum computer uptime and make their hardware more accessible by automating the tuning process.