Skip to content
SPECIFICTION
Get listed

ZenML

zenml.io

From $999/mo Free plan WebWindowsmacOSLinuxAPISelf-hosted
Visit zenml.io
Spec score 8.4 #9 of 38 in Model registries

What it is

ZenML orchestrates AI and machine-learning pipelines and agents written in Python. Pipelines can run on Kubernetes, Vertex AI, SageMaker, AzureML, or a laptop without rewriting code. ZenML versions step outputs such as models and evaluation datasets, supports re-execution from any step, and reuses cached results when code and inputs have not changed. Deployment choices include local, SaaS, and self-hosted setups, with Docker and Kubernetes Helm methods. ZenML says it stores metadata while data, artifacts, and compute remain in the customer's infrastructure or VPC. Its integrations directory lists 66 tools, including LangGraph, OpenAI Agents SDK, PyTorch, MLflow, AWS, and Google Cloud Vertex AI Pipelines. The self-hosted Open Source plan is free and includes unlimited executions and projects. Scale costs $999 a month and includes 2,000 executions, three projects, and five snapshots. Enterprise has custom pricing and adds SSO, custom-role RBAC, audit logs, and air-gapped deployment. ZenML says it is SOC 2 Type II and ISO 27001 certified.

Spec sheet

Purpose
ZenML orchestrates AI and machine-learning pipelines and agents written in Python.Read 30 Sep 2026 · zenml.io
Deployment
ZenML supports local, SaaS, and self-hosted deployment, including Docker and Kubernetes Helm deployment methods.Read 30 Sep 2026 · zenml.io
Integrations
The integrations directory lists 66 tools, including LangGraph, OpenAI Agents SDK, PyTorch, MLflow, AWS, and Google Cloud Vertex AI Pipelines.Read 30 Sep 2026 · zenml.io
Security
ZenML states that it is SOC 2 Type II and ISO 27001 certified.Read 30 Sep 2026 · zenml.io
Support
The Open Source plan includes community support, Scale includes priority support, and Enterprise includes dedicated support with an SLA.Read 30 Sep 2026 · zenml.io
Headquarters
Munich, GermanyRead 28 Sep 2026 · zenml.io
Artifact versioning
ZenML versions step results, including models and evaluation datasets, and supports re-execution from any step.Read 30 Sep 2026 · zenml.io
Caching
ZenML caches step results and reuses them when code and inputs have not changed.Read 30 Sep 2026 · zenml.io
Data handling
ZenML says it stores metadata while data, artifacts, and compute stay in the customer's infrastructure or VPC.Read 30 Sep 2026 · zenml.io
Enterprise controls
The Enterprise plan adds SSO, custom-role RBAC, audit logs, and air-gapped deployment.Read 30 Sep 2026 · zenml.io
Infrastructure
Pipelines can run on Kubernetes, Vertex AI, SageMaker, AzureML, or a laptop without rewriting the code.Read 30 Sep 2026 · zenml.io
Overage
ZenML says it does not cut off service for occasional monthly execution overages and may contact customers if overages become a pattern.Read 30 Sep 2026 · zenml.io
Target users
The Open Source plan is described for individuals and small teams, Scale for teams running ML in production, and Enterprise for organizations at scale.Read 30 Sep 2026 · zenml.io

Plans and prices

Open Source Free Unlimited executions · Unlimited projects · Self-hosted Read 30 Sep 2026 · zenml.io
Scale $999 a month Monthly executions, per workspace 2,000 executions · 3 projects · 5 snapshots Read 30 Sep 2026 · zenml.io
Enterprise Priced on request Custom Unlimited executions · Unlimited projects · SSO · Custom-role RBAC · Audit logs · Air-gapped deployment Read 30 Sep 2026 · zenml.io

Every ZenML plan and price →

Strong points and limits

Strong points

  • Run pipelines across cloud services, Kubernetes, or a laptop.
  • Version outputs and re-execute from any step.
  • Free self-hosted plan includes unlimited executions and projects.
  • Metadata stays separate from customer data and compute.
  • Enterprise includes SSO, audit logs, and air-gapped deployment.

Limits

  • Scale costs $999 a month.
  • Scale includes 2,000 executions, three projects, and five snapshots.
  • Enterprise pricing is custom.

Who it suits

The Open Source plan is described for individuals and small teams; Scale targets teams running ML in production. Enterprise is aimed at organizations operating at scale.

Verdict

ZenML provides pipeline orchestration with versioning, caching, and deployment choices spanning local and self-hosted environments. Teams should compare the Scale execution and project allowances with their needs; Enterprise pricing is custom.

Where Specifiction places it

Alternatives to ZenMLAll alternatives →