List of Microsoft Azure Quantum Computing Customers
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United States
Since 2010, our global team of researchers has been studying Microsoft Azure Quantum Computing customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased Microsoft Azure Quantum Computing for Cognitive Computing from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using Microsoft Azure Quantum Computing for Cognitive Computing include: Microsoft, a United States based Professional Services organisation with 221000 employees and revenues of $243.00 billion, Pacific Northwest National Laboratory, a United States based Government organisation with 6400 employees and revenues of $1.64 billion, Case Western Reserve University, a United States based Education organisation with 4147 employees and revenues of $1.30 billion and many others.
Contact us if you need a completed and verified list of companies using Microsoft Azure Quantum Computing, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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Case Western Reserve University | Education | 4147 | $1.3B | United States | Microsoft | Microsoft Azure Quantum Computing | Cognitive Computing | 2018 | n/a |
In 2018, Case Western Reserve University worked with Microsoft's quantum team to apply Microsoft Azure Quantum Computing to magnetic resonance fingerprinting for medical imaging research in the United States. The effort used Microsoft Azure Quantum Computing within a Cognitive Computing framework to evaluate quantum inspired algorithms for MRI signal processing and prototype research workloads. The implementation ran quantum inspired algorithms on classical Azure infrastructure, aligning compute provisioning and algorithm orchestration with cloud based experimentation.
The deployment focused on algorithm modules for magnetic resonance fingerprinting, embedding quantum inspired routines into MRI acquisition and fingerprinting pipelines and configuring them to execute as cloud based compute tasks during imaging experiments. Microsoft Azure Quantum Computing was used to host and manage the algorithm execution environment while data flows remained within university research pipelines for preprocessing and postprocessing.
Operational scope covered medical imaging research at Case Western Reserve University in the United States, with university research labs adjusting workflows to incorporate algorithm runs and validation studies. Governance centered on collaborative research protocols with Microsoft quantum specialists, with experimental controls and validation procedures applied to integrate algorithm outputs into imaging analysis.
Results published from the collaboration reported MRI scans up to three times faster and roughly 30 percent improved precision in research prototypes, demonstrating concrete experimental outcomes from applying Microsoft Azure Quantum Computing and quantum inspired algorithms to magnetic resonance fingerprinting.
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Microsoft | Professional Services | 221000 | $243.0B | United States | Microsoft | Microsoft Azure Quantum Computing | Cognitive Computing | 2022 | n/a |
In 2022, Microsoft deployed Microsoft Azure Quantum Computing, a Cognitive Computing application, to support the Azure Storage team. The deployment targeted infrastructure and storage operations across the United States and was executed within the Microsoft Azure environment to address cluster load balancing challenges.
The implementation leveraged Microsoft Azure Quantum Computing's quantum inspired optimization capability to rebalance data placement and workload distribution across storage clusters. Implementation focused on operationalizing optimization outputs for cluster balancing decisions and capacity allocation, aligning optimization inputs with existing storage operational processes.
Reported outcomes included a fourfold reduction in the number of hot clusters, a tenfold reduction in monthly support escalations, and approximately an 8 percent improvement in regional storage load uniformity, all within the targeted infrastructure and storage operations scope.
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Pacific Northwest National Laboratory | Government | 6400 | $1.6B | United States | Microsoft | Microsoft Azure Quantum Computing | Cognitive Computing | 2024 | n/a |
In 2024 Pacific Northwest National Laboratory partnered with Microsoft to deploy Microsoft Azure Quantum Computing using Azure Quantum Elements to accelerate materials discovery for energy storage. The initiative is categorized as Cognitive Computing and targeted scientific discovery workflows in materials science research in the United States.
The implementation centered on Azure Quantum Elements capabilities, combining AI model training and high performance computing simulation alongside quantum and quantum inspired compute methods to shorten candidate screening cycles. Configuration emphasized workload orchestration for simulation and inference, enabling rapid proof of concept runs that integrated AI driven property prediction with HPC scale simulations.
Operational scope covered PNNL research groups focused on energy storage materials and electrolyte discovery, with collaborative governance between PNNL scientists and Microsoft technical teams to coordinate experiment pipelines and compute provisioning. The R&D collaboration delivered a rapid proof of concept and identified a new electrolyte candidate that could substantially reduce lithium usage, demonstrating Microsoft Azure Quantum Computing applied to materials science research and scientific discovery workflows under the Cognitive Computing category.
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