# Welcome to ZenML

ZenML is a unified MLOps framework that extends the battle-tested principles you rely on for classical ML to the new world of AI agents. It's one platform to develop, evaluate, and deploy your entire AI portfolio - from decision trees to complex multi-agent systems. By providing a single framework for your entire AI stack, ZenML enables developers across your organization to collaborate more effectively without maintaining separate toolchains for models and agents.

### Getting Started

<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>Installation</strong></td><td>Set up ZenML in your environment</td><td><a href="https://1640328923-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F5aBlTJNbVDkrxJp7J1J9%2Fuploads%2Fgit-blob-50bfe7f52b8c0609e52d3a73ac784551f47c9547%2Fproduction.png?alt=media">production.png</a></td><td><a href="installation">installation</a></td></tr><tr><td><strong>Core Concepts</strong></td><td>Understand ZenML fundamentals</td><td><a href="https://1640328923-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F5aBlTJNbVDkrxJp7J1J9%2Fuploads%2Fgit-blob-69f92c74a76764494a3a4b828bd10544d67610f1%2Fcore-concepts.png?alt=media">core-concepts.png</a></td><td><a href="core-concepts">core-concepts</a></td></tr><tr><td><strong>Hello World</strong></td><td>Build your first ML workflow</td><td><a href="https://1640328923-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F5aBlTJNbVDkrxJp7J1J9%2Fuploads%2Fgit-blob-f0e3ad28698ba20b3a65579c16e5769f86c8c07c%2Fhow-to.png?alt=media">how-to.png</a></td><td><a href="hello-world">hello-world</a></td></tr></tbody></table>

If you use AI coding tools, see [LLM tooling](https://docs.zenml.io/reference/llms-txt) 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="https://1640328923-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F5aBlTJNbVDkrxJp7J1J9%2Fuploads%2Fgit-blob-ba28e91d285ed45c61379aa512a6afe4eddfb5f2%2Fstarter.png?alt=media">starter.png</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="https://1640328923-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F5aBlTJNbVDkrxJp7J1J9%2Fuploads%2Fgit-blob-3ab5bd3c872a40e6ea60b298af84464f0515ed95%2Fprod.png?alt=media">prod.png</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>LLMOps Guide</strong></td><td>Build and deploy Large Language Model pipelines</td><td><a href="https://1640328923-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F5aBlTJNbVDkrxJp7J1J9%2Fuploads%2Fgit-blob-b60949cc86e9fc4e8857f368a772464469444e99%2Fllm.png?alt=media">llm.png</a></td><td><a href="https://docs.zenml.io/user-guides/llmops-guide">https://docs.zenml.io/user-guides/llmops-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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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.zenml.io/getting-started/introduction.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
