Kubeflow
Engineering Software · California, United States · 51-200 Employees
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Overview
Headquarters
Mountain View, California, United StatesWebsite
www.kubeflow.orgRevenue
<$5 MillionIndustry
ZI Rank: 1
Signal Type
Mar
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ZI Rank
1
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About Kubeflow
Kubeflow is a foundation of tools designed for AI platforms on Kubernetes, enabling AI platform teams to build and deploy machine learning workflows efficiently. The platform is modular, portable, and scalable, supporting various stages of the AI lifecycle. Key components include Kubeflow Pipelines for workflow management, Kubeflow Notebooks for interactive development, and Kubeflow KServe for AI inference. Kubeflow is an open-source project backed by a community of developers and organizations, making it a trusted choice for deploying machine learning applications.Explore more
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Revenue
Number of Employees
Type
Funding
Founded In
$52.5M
201-500
Private
-
2001
RH
Rohan HardieChief Financial Officer, Executive Director & Company Secretary
$15.1M
11-50
Private
<$5M
2011
AL
Alberto LasarteVice President, Partnerships Strategic Alliances & Strategic Advisor
Company Profile Activity
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Kubeflow is experiencing very low activity levels compared to other companies in the Software sector.
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Kubeflow Tech Stack
A closer look at the technologies used by Kubeflow
Kubeflow News & Media
Open source Kubeflow 1.7 set to ‘transform’ MLops
Kubeflow 1.7 became generally available today (March 29), providing the first update to the widely used open source MLops platform since the debut of Kubeflow 1.6 in Sept. 2022. At its core, Kubeflow is an open source ML toolkit that helps organizations to deploy and run ML workflows on cloud-native Kubernetes infrastructure. Among the themes of the Kubeflow 1.7 update is a focus on helping to better support transformer based models.Kubernetes ML optimizer, Kubeflow, improves data preprocessing with v1.6
Kubernetes optimizer for machine learning, Kubeflow, has released v1.6, with security updates, improved runtimes and updated AI modeling.Comet Expands Alliances Across the Complete Machine Learning Lifecycle
NEW YORK--(BUSINESS WIRE)-- #AI--Comet, provider of the leading development platform for machine learning (ML) teams from startup to enterprise, today announced several integrations – including Ray, Kubeflow, and Google Vertex AI – that will eliminate complexity, provide optionality, and bolster scalability across the entire machine learning lifecycle. These integrations deliver on Comet’s commitment to providing a ML platform that allows data scientists and ML practitioners to use the best toolIBM open-sources Kubeflow Pipelines on Tekton for portable machine learning models
IBM Corp. said today it’s hoping to provide a standardized solution for developers to create and deploy machine learning models in production and make them portable to any cloud platform. To do so, it said it’s open-sourcing the Kubeflow machine learning platform on Tekton, a continuous integration/continuous development platform developed by Google LLC. It’s popular […] The post IBM open-sources Kubeflow Pipelines on Tekton for portable machine learning models appeared first on SiliconANGLE.
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Kubeflow is a foundation of tools designed for AI platforms on Kubernetes, enabling AI platform teams to build and deploy machine learning workflows efficiently. The platform is modular, portable, and scalable, supporting various stages of the AI lifecycle. Key components include Kubeflow Pipelines for workflow management, Kubeflow Notebooks for in... Read More
