Kubeflow
NewThe Open Source AI Platform
Data collected ·ChatGPT, Perplexity, Google AI Mode·coverage 100%·next run
- Kubeflow ranks #9 of 61 in MLOps Platforms with an AI visibility score of 20.1 (SlateIndex, Nov 2, 2026).
- Kubeflow is most visible on Google AI Mode (20.6) and least on ChatGPT (19.1).
- AI engines name Kubeflow in 22 of the 30 MLOps Platforms buyer prompts SlateIndex tracks.
- ones.com is the source AI engines cite most in answers about Kubeflow, with 18 citations.
About
Company details for Kubeflow
Kubeflow is an open source platform for running machine learning and AI workloads on Kubernetes. It is made of modular subprojects covering pipelines, model training, hyperparameter tuning, notebooks, a model registry and a central dashboard. The core project is free under the Apache 2.0 license and is a CNCF graduated project. It ranks #9 of 61 in MLOps Platforms on SlateIndex and has a visibility score of 20.1 in the latest weekly run.
Founded in 2017 and headquartered in Sunnyvale, CA, United States, the company employs 51–200 people. Its differentiator: a Kubernetes-native, modular stack for data and AI workloads that runs the same code on a laptop, on-premises or in any cloud.
- Website
- kubeflow.org
- Categories
- MLOps Platforms
- Company size
- 51–200 employees
- Headquarters
- Sunnyvale, CA, United States
- Founded
- 2017
- Company type
- Open source project
- Deployment
- Runs as a collection of microservices on any Kubernetes cluster, including on-premises, hybrid, and AWS, Azure, or GCP.
- Platforms
- Kubernetes, On-premises, AWS, Azure, Google Cloud
- Support
- Weekly community calls, Mailing list, Slack workspace
Read from linkedin.com, github.com, kubeflow.org, 7wdata.be, cncf.io · refreshed Nov 2, 2026.
AI visibility
Latest weekly run · Nov 2 · next run Nov 9
Visibility score trend
Weekly runs over the last 60 days, with up to 7 competitors. Click a name to hide or show its line.
Changes appear after the second weekly run in MLOps Platforms. MLflow leads the category at 50.9%.
Media
Website and product screenshots for Kubeflow
AI mentions & citations
Recent answers that name Kubeflow
Alternatives to the most popular MLOps platform
As of November 2026, the strongest alternatives to the leading MLOps platforms include ClearML, Kubeflow, ZenML, Weights & Biases, Amazon SageMaker, and Comet.
How much does an MLOps platform cost per month?
What features matter most in an MLOps platform?
Are you looking for open-source tools (like MLflow/Kubeflow) or commercial enterprise platforms (like Databricks/SageMaker)?
How long does it take to roll out an MLOps platform?
buy (e.g., using open-source tools like MLflow/Kubeflow versus commercial platforms), and auditing existing data infrastructure.
How much does an MLOps platform cost per month?
Examples: MLflow, Kubeflow, ZenML (open-source core), and BentoML.
How much does an MLOps platform cost per month?
MLflow, Kubeflow, and ClearML are examples.
What is the typical pricing model for MLOps Platforms software?
Free or open-source self-hosting: Tools such as MLflow and Kubeflow have no software license fee, but you pay for cloud infrastructure and engineering effort.
What is the difference between an MLOps platform and a data science platform?
Typical Tools: MLflow, Kubeflow, BentoML, Airflow, Docker, Kubernetes, and enterprise cloud monitoring services.
Products & features
What Kubeflow sells
Kubeflow Spark Operator
Makes specifying and running Spark applications as easy as running other workloads on Kubernetes.
Kubeflow Notebooks
Runs interactive development environments for AI, ML, and Data workloads on Kubernetes.
Kubeflow Trainer
Kubernetes-native distributed training and LLM fine-tuning across frameworks such as PyTorch, JAX, HuggingFace and XGBoost.
Kubeflow Katib
Kubernetes-native AutoML with hyperparameter tuning, early stopping and neural architecture search.
Kubeflow Hub
Formerly Model Registry; indexes and manages models, versions and ML artifact metadata.
Kubeflow Pipelines
Platform for building and deploying portable, scalable machine learning workflows on Kubernetes.
Kubeflow Dashboard
Central dashboard that connects the authenticated web interfaces of Kubeflow and other ecosystem components.
Strengths engines cite
- free and open source
- strong choice for Kubernetes-native, cloud-native ML platforms
- portability and deep infrastructure control
- modular, open-source infrastructure
Target market & buyers
AI practitioners, platform administrators, and decision-makers working with data, AI/ML and HPC workloads on Kubernetes.
Notable customers include Bloomberg, NVIDIA, Red Hat, LinkedIn, Spotify.
Funding & recent developments
Funding
| Latest known round | Total raised |
|---|---|
| — | — |
Recent developments
- Aug 2026CompanyKubeflow graduates as a CNCF project
The CNCF announced Kubeflow's graduation, after a formal steering committee, Code of Conduct adoption and a third-party security audit were in place.
- Aug 2026ProductKubeflow MCP announced
Kubeflow MCP, an interface that lets AI agents operate Kubeflow, was announced.
- Jun 2026SecurityThird-party security audit published
An ADA Logics audit arranged through OSTIF and the CNCF covered six Kubeflow subprojects and reported 14 findings with security impact.
- Mar 2026ProductKubeflow 26.03 released
Kubeflow 26.03 was released.
- Dec 2025ProductKubeflow 1.11 rebranded as AI Reference Platform
Kubeflow 1.11 was rebranded as the Kubeflow AI Reference Platform and introduced the Kubeflow SDK.
Competitive landscape
How Kubeflow compares with its top three alternatives
Kubeflow most often appears alongside MLflow, Amazon SageMaker AI, AWS in AI answers.
| Brand | Visibility | Share of voice | vs last week | Starting price |
|---|---|---|---|---|
| Kubeflow | 20.1% | 5.8% | New | Pricing not available |
| MLflow | 50.9% | 9.7% | New | Pricing not available |
| Amazon SageMaker AI | 44.4% | 8% | New | Pricing not available |
| AWS | 35.7% | 7.5% | New | Pricing not available |
| Google Vertex AI | 33.1% | 7.2% | New | Pricing not available |
What AI answers say
Sentiment and themes from the answers that mention this brand
Positive 17% · Neutral 59% · Mixed 24% of 41 engine answers that mention Kubeflow
Praised for
- free and open source
- strong choice for Kubernetes-native, cloud-native ML platforms
- portability and deep infrastructure control
- modular, open-source infrastructure
Criticised for
- operationally complex, especially for small teams
- requires Kubernetes expertise and significant infrastructure ownership
- Kubernetes operations add infrastructure costs
Cite as: SlateIndex, “Kubeflow AI visibility profile”, https://slateindex.ai/brand/kubeflow, data of Nov 2, 2026. Licence: CC BY 4.0.