# Create and deploy a custom model

> Create and deploy a custom model - Create, deploy, and monitor a custom inference model with
> DataRobot's Python client.

This Markdown file sits beside the HTML page at the same path (with a `.md` suffix). It summarizes the topic and lists links for tools and LLM context.

Companion generated at `2026-05-06T18:17:09.574528+00:00` (UTC).

## Primary page

- [Create and deploy a custom model](https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/custom-model-dev/create-custom-model.html): Full documentation for this topic (HTML).

## Related documentation

- [Developer documentation](https://docs.datarobot.com/en/docs/api/index.html): Linked from this page.
- [Developer learning](https://docs.datarobot.com/en/docs/api/dev-learning/index.html): Linked from this page.
- [AI accelerators](https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/index.html): Linked from this page.
- [Custom model development](https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/custom-model-dev/index.html): Linked from this page.

## Documentation content

[Access this AI accelerator on GitHub](https://github.com/datarobot-community/ai-accelerators/blob/27a757bcf3b10374e70d4c406058ef9cafd28524/ecosystem_integration_templates/Custom%20Model%20End-to-End%20With%20Compliance%20Docs/Custom%20Model%20End-to-End%20With%20Compliance%20Docs.ipynb)

This accelerator outlines how to create, deploy, and monitor a custom inference model with DataRobot's Python client. You can use the Custom Model Workshop to upload a model artifact to create, test, and deploy custom inference models to DataRobot’s centralized deployment hub.