> For the complete documentation index, see [llms.txt](https://docs.zenml.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.zenml.io/getting-started/introduction.md).

# Welcome to ZenML

ZenML is an open-source framework for developing, evaluating, and deploying your entire AI portfolio: classical ML, LLM pipelines, and AI agents alike. It brings the battle-tested engineering principles of production ML to everything you ship, so you don't maintain one toolchain for models and another for agents.

That story has two open-source projects behind it:

* **ZenML** is the MLOps framework: portable, production-ready **pipelines** for ML and LLM workloads, with versioned artifacts, caching, and infrastructure abstracted behind [stacks](https://docs.zenml.io/stacks).
* [**Kitaru**](https://docs.zenml.io/kitaru) is for **AI agents**: run, replay, improve. It records every model call and tool call as a durable checkpoint, so you can replay a real run with one thing changed, diff the two, and roll the winning change across a cohort of runs.

Each works on its own. You can run ZenML and never touch Kitaru, or pick up Kitaru purely to make one agent durable. If you do use both, they compose rather than coexist: a Kitaru flow is a dynamic ZenML pipeline under the hood, so your agents and pipelines run on the same stacks, persist artifacts to the same stores, and show up in the same server and dashboard.

### What are you building?

Pick the path that matches your work. Neither path requires the other, and adopting the second one later doesn't mean starting over.

<table data-view="cards"><thead><tr><th></th><th></th><th data-hidden data-card-cover data-type="files"></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td><strong>ML Pipelines → ZenML</strong></td><td>Build, version, and deploy classical ML and LLM pipelines. Start with Hello World, then the Starter guide.</td><td><a href="/files/qdeGD5qx5b8tXE5MV5SE">/files/qdeGD5qx5b8tXE5MV5SE</a></td><td><a href="/pages/hMvaw3pJYHjAQ2mQuRGb">/pages/hMvaw3pJYHjAQ2mQuRGb</a></td></tr><tr><td><strong>AI Agents → Kitaru</strong></td><td>Run agents durably, replay any run with one change, and keep the version that wins on cost, latency, and quality. Start with the Agents guide, or jump to the Kitaru quickstart.</td><td><a href="/files/YfFG4p4r8KCz7DiIUP1s">/files/YfFG4p4r8KCz7DiIUP1s</a></td><td><a href="https://docs.zenml.io/user-guides/agents-guide">https://docs.zenml.io/user-guides/agents-guide</a></td></tr></tbody></table>

### How these docs are organized

The documentation is split into spaces — the tabs at the top of this page. Knowing what lives where saves you a lot of searching:

| Space                                                                                                               | What you'll find there                                                                                                |
| ------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------- |
| **ZenML** (you are here)                                                                                            | The pipelines framework: installation, core concepts, deployment, and how-to guides                                   |
| [**Kitaru**](https://docs.zenml.io/kitaru)                                                                          | The agents project: quickstart, flows and checkpoints, replay and execution management, framework adapters            |
| [**Learn**](https://docs.zenml.io/user-guides)                                                                      | Narrative guides for both projects: Starter, Production, LLMOps, and Agents tracks, plus tutorials and best practices |
| [**Stacks**](https://docs.zenml.io/stacks)                                                                          | The infrastructure components — orchestrators, artifact stores, and more — that both pipelines and agents run on      |
| [**SDK reference**](https://docs.zenml.io/sdk-reference) / [**API reference**](https://docs.zenml.io/api-reference) | Client and REST API references, organized per project                                                                 |
| [**Changelog**](https://docs.zenml.io/changelog)                                                                    | Release notes, version by version                                                                                     |

### First steps

Whichever path you picked, the first steps are the same shape: install, run something real, then learn the concepts.

|               | ML Pipelines (ZenML)                               | AI Agents (Kitaru)                                                        |
| ------------- | -------------------------------------------------- | ------------------------------------------------------------------------- |
| **Install**   | [Installation](/getting-started/installation.md)   | [Installation](https://docs.zenml.io/kitaru/getting-started/installation) |
| **First run** | [Hello World](/getting-started/hello-world.md)     | [Quickstart](https://docs.zenml.io/kitaru/getting-started/quickstart)     |
| **Concepts**  | [Core Concepts](/getting-started/core-concepts.md) | [Core Concepts](https://docs.zenml.io/kitaru/concepts)                    |

If you use AI coding tools, see [LLM tooling](/reference/llms-txt.md) for ZenML's MCP server and Agent Skills (including `zenml-scoping` and `zenml-pipeline-authoring`).

### Guides

<table data-view="cards"><thead><tr><th></th><th></th><th data-hidden data-card-cover data-type="files"></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td><strong>Starter Guide</strong></td><td>Get started with ZenML fundamentals and set up your first pipeline</td><td><a href="/files/qyUjfZIIZ6gu6KN2d1i0">/files/qyUjfZIIZ6gu6KN2d1i0</a></td><td><a href="https://docs.zenml.io/user-guides/starter-guide">https://docs.zenml.io/user-guides/starter-guide</a></td></tr><tr><td><strong>Production Guide</strong></td><td>Move your ML pipelines from development to production</td><td><a href="/files/MdXKmxkxJ3qzq1imbM3J">/files/MdXKmxkxJ3qzq1imbM3J</a></td><td><a href="https://docs.zenml.io/user-guides/production-guide">https://docs.zenml.io/user-guides/production-guide</a></td></tr><tr><td><strong>Agents Guide</strong></td><td>Run agents durably, replay a real run with one change, and improve them across a cohort with Kitaru</td><td><a href="/files/YfFG4p4r8KCz7DiIUP1s">/files/YfFG4p4r8KCz7DiIUP1s</a></td><td><a href="https://docs.zenml.io/user-guides/agents-guide">https://docs.zenml.io/user-guides/agents-guide</a></td></tr></tbody></table>

<figure><img src="https://static.scarf.sh/a.png?x-pxid=f0b4f458-0a54-4fcd-aa95-d5ee424815bc" alt="ZenML Scarf"><figcaption></figcaption></figure>


---

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