List of Kubeflow Customers
Since 2010, our global team of researchers has been studying Kubeflow 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 Kubeflow for MLOps Platforms 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 Kubeflow for MLOps Platforms include: Babylon Health, a United Kingdom based Professional Services organisation with 2147 employees and revenues of $1.11 billion, Cern, a Switzerland based Non Profit organisation with 2500 employees and revenues of $600.0 million, ROSEN Group, a United States based Professional Services organisation with 4000 employees and revenues of $600.0 million and many others.
Contact us if you need a completed and verified list of companies using Kubeflow, 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.
The Kubeflow customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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Babylon Health | Professional Services | 2147 | $1.1B | United Kingdom | Kubeflow | Kubeflow | MLOps Platforms | 2019 | n/a |
In 2019, Babylon Health deployed Kubeflow on its Kubernetes platform to build a self-service AI training platform for medical and clinical ML workflows in the United Kingdom. Kubeflow served as the MLOps Platforms component to centralize model training, experiment orchestration, and researcher access to compute.
The implementation configured Kubeflow pipelines and notebook-based workflows to enable experiment orchestration, reproducible training runs, and dataset locality so researchers could run experiments close to patient data. The self-service environment provided role-based access to compute resources and automated job scheduling consistent with MLOps Platforms capabilities.
The deployment was hosted on Babylon Health's Kubernetes cluster, integrating cluster resource management with Kubeflow to allocate GPUs and CPU for clinical ML workloads. Operational scope covered clinical research teams and healthcare model validation workflows within the UK, focusing on clinical model training and validation pipelines.
Governance centralized experiment tracking, reproducible pipelines, and researcher provisioning to accelerate iteration cycles while maintaining controlled access to sensitive data. The move cut clinical validation time from around 10 hours to under 20 minutes and improved researcher access to compute resources for faster model iteration.
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Cern | Non Profit | 2500 | $600M | Switzerland | Kubeflow | Kubeflow | MLOps Platforms | 2020 | n/a |
In 2020 Cern implemented Kubeflow as its MLOps Platforms backbone, provisioning an internal service named ml.cern.ch to manage the full machine learning lifecycle for physics and scientific research workloads. The deployment centralizes experimentation and pipeline orchestration to serve the institute's user community across Europe.
The Kubeflow implementation emphasizes capabilities for large scale distributed training, automated hyperparameter tuning, and model serving, delivering an end to end pipeline orchestration layer and experiment management for researcher workflows. Configuration includes GPU resource scheduling and distributed compute management to support research scale training jobs and multi node training frameworks.
Operated as an internal, centrally managed platform, ml.cern.ch runs GPU backed experiments and orchestrates model deployments for physics research. The implementation accelerates research workflows and scales GPU backed experiments across the European user community, while governance is organized through the internal platform service model and research computing operations.
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ROSEN Group | Professional Services | 4000 | $600M | United States | Kubeflow | Kubeflow | MLOps Platforms | 2023 | n/a |
In 2023, ROSEN Group deployed Kubeflow as its MLOps Platforms implementation to power AI-driven pipeline inspection and asset analytics for its energy sector operations in Germany. The Kubeflow deployment was oriented around high-throughput model training and model serving workflows to support inspection throughput and analytics delivery to engineering and asset management teams.
The implementation emphasized core MLOps capabilities common to the category, including orchestration of end-to-end pipelines, automated model training and serving, and experiment tracking to manage model lifecycle and reproducibility. Kubeflow was configured to support large-scale data ingestion and batch training workloads, enabling iterative model development and production serving for inspection analytics.
Architecturally the platform was run with containerized compute and a persistent storage layer integrated using Portworx and Pure Storage, providing the durable, high-throughput storage needed for model training and serving. During pilot operations the environment processed 150 TB of data, demonstrating the storage and I O capacity required for asset analytics workloads.
Governance and rollout were exercised through a pilot phase focused on pipeline inspection use cases, with operational coverage in Germany and alignment to engineering and analytics functions. The pilot reported approximately 70% reduction in time to deliver analyses to customers, improving inspection throughput and insight delivery, and the Kubeflow MLOps Platforms deployment established foundation-level workflows for continued model iteration and productionization.
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Buyer Intent: Companies Evaluating Kubeflow
- Public Services and Procurement Canada, a Canada based Government organization with 17000 Employees
- Samsung Electronics, a South Korea based Manufacturing company with 262647 Employees
Discover Software Buyers actively Evaluating Enterprise Applications
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