Metaflow

Enterprise-grade MLOps platform for scalable, compliant data science workflows

MLOpsData ScienceWorkflow AutomationScalability

About

Metaflow enables enterprises to build and manage real-life data science projects with ease, ensuring scalability and reliability at production scale. It supports compliance and governance requirements, facilitating collaboration across teams while integrating seamlessly with existing infrastructure.

This description came from a bulk import and has not yet been checked against the vendor's own page. Treat it as unverified.

Enterprise Readiness

from cataloged data

Not scored. Nobody has checked this entry against Metaflow’s own site yet, so the signals below are unverified and we will not turn them into a rating. The breakdown shows what our record holds.

Security & ComplianceNot disclosed

No compliance certifications listed

Deployment FlexibilityStrong

Flexible deployment: Cloud, On-Premise, Hybrid, Self-Hosted

Integration DepthStrong

8 documented integrations

Proven AdoptionPartial

6 documented use cases

Company MaturityPartial

Founded 2017

Composite of public compliance, deployment, integration, adoption, and company signals. “Not disclosed” reflects gaps in available data, not a vendor deficiency.

Independently sourced

Pulled directly from regulator filings and platform APIs. No vendor or editorial input.

Activity classifier

Dormant

no commits or releases in 105 months

GitHub API2026-05-27

metaflow-ai

SDK / client libraries· 165★· active 8.9y ago

Python · CSS

OSV vulnerability feed2026-08-24

No known advisories

Enterprise Use Cases

End-to-end machine learning workflow management

Scalable model training and deployment

Data pipeline orchestration for ML projects

Collaboration across data science and engineering teams

Governance and compliance in ML lifecycle

Integration with cloud and on-premise infrastructure

Integrations

AWSKubernetesDockerTensorFlowPyTorchSlackAirflowSnowflake

How Metaflow compares

Tool	Readiness	Pricing	Deployment	Compliance	Integrations
Metaflow	Not scored	Open Source	Cloud, On-Premise, Hybrid, Self-Hosted	—	8
Groq	Not scored	Enterprise	Cloud, On-Premise, Hybrid, Self-Hosted	—	8
Weights & Biases W&B	Not scored	Freemium	Cloud, On-Premise, Hybrid, Self-Hosted	—	8
Comet ML Platform	70 · Strong	Enterprise	Cloud, On-Premise, Hybrid, Self-Hosted	—	8

Peers from the same category, ranked by Enterprise Readiness. Readiness is a composite of cataloged compliance, deployment, integration, adoption, and company signals.

Frequently Asked Questions

What is Metaflow used for?

Metaflow is enterprise-grade MLOps platform for scalable, compliant data science workflows. It is commonly used for end-to-end machine learning workflow management, scalable model training and deployment, data pipeline orchestration for ml projects, and collaboration across data science and engineering teams.

Is Metaflow free, and how is it priced?

Metaflow is open source and can be self-hosted at no licensing cost. Commercial support or hosted tiers may also be available from the vendor.

How can Metaflow be deployed?

Metaflow supports Cloud, On-Premise, Hybrid, and Self-Hosted deployment. On-premise and self-hosted options support data-residency and air-gapped requirements.

What does Metaflow integrate with?

Metaflow documents 8 integrations, including AWS, Kubernetes, Docker, TensorFlow, PyTorch, and Slack.

When was Metaflow founded?

Metaflow was founded in 2017.

Is Metaflow enterprise-ready?

Based on cataloged data, Metaflow has an Enterprise Readiness score of 64/100 (Established tier), derived from its compliance, deployment, integration, adoption, and company-maturity signals.

Quick Facts

PricingOpen Source

DeploymentCloud, On-Premise, Hybrid, Self-Hosted

Founded2017

CategoryData & MLOps

Procurement

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