Strangeworks vs a2z Radiology AI
Side-by-side comparison of AI visibility scores, market position, and capabilities
Quantum computing platform aggregating hardware from IBM, IonQ, Rigetti, and D-Wave for enterprise customers; Austin TX;
About
Strangeworks is an Austin-based quantum computing platform company that provides enterprise customers with a unified development environment for accessing and comparing quantum hardware from multiple vendors including IBM, IonQ, Rigetti, and D-Wave, alongside simulators and classical HPC resources. The platform abstracts the complexity of working with different quantum hardware APIs, enabling developers to write algorithms once and run them on the most appropriate hardware for their specific problem. Strangeworks QC (formerly known as the Quantum Computing Inc. platform) provides collaboration tools, quantum circuit editors, and enterprise access controls for teams building quantum applications. The company helps enterprises at the earliest stages of quantum computing adoption — identifying relevant use cases, building quantum literacy within technical teams, and experimenting with quantum algorithms before commercial quantum advantage arrives. Founded in 2018 by former IBM executive William Hurley, Strangeworks raised seed funding from investors including IBM Ventures and 5 Ventures. It competes with Amazon Braket, Azure Quantum, and IBM Quantum in the quantum computing access platform market.
a2z Radiology AI raised $20M in 2025 for its whole-body AI that simultaneously screens for 24+ conditions across CT scans — from incidental cancers to cardiovascular risk — in a single automated read.
About
a2z Radiology AI has developed a whole-body CT analysis platform that simultaneously screens for over 24 medical conditions across a single CT scan, including incidental cancers, coronary artery disease, aortic aneurysm, bone density loss, and organ abnormalities. The AI acts as a second reader that radiologists can use to catch incidental findings that fall outside the primary reason for a scan — a major source of missed diagnoses.
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