> For the complete documentation index, see [llms.txt](https://docs.n8n.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.n8n.io/deploy/host-n8n/deploy-with-the-ai-starter-kit.md).

# Deploy with the AI starter kit

The Self-hosted AI Starter Kit is an open, docker compose template that bootstraps a fully featured Local AI and Low Code development environment.

Curated by [n8n](https://github.com/n8n-io), it combines the self-hosted n8n platform with a list of compatible AI products and components to get you started building self-hosted AI workflows.

## What’s included <a href="#whats-included" id="whats-included"></a>

✅ [**Self-hosted n8n**](/deploy/host-n8n.md): Low-code platform with over 400 integrations and advanced AI components.

✅ [**Ollama**](https://ollama.com/): Cross-platform LLM platform to install and run the latest local LLMs.

✅ [**Qdrant**](https://qdrant.tech/): Open-source, high performance vector store with a comprehensive API.

✅ [**PostgreSQL**](https://www.postgresql.org/): The workhorse of the Data Engineering world, handles large amounts of data safely.

## What you can build <a href="#what-you-can-build" id="what-you-can-build"></a>

⭐️ [AI Agents](#user-content-fn-1)[^1]{ data-preview} that can schedule appointments

⭐️ Summaries of company PDFs without leaking data

⭐️ Smarter Slackbots for company communications and IT-ops

⭐️ Private, low-cost analyses of financial documents

## Get the kit <a href="#get-the-kit" id="get-the-kit"></a>

Head to [the GitHub repository](https://github.com/n8n-io/self-hosted-ai-starter-kit) to clone the repo and get started!

{% hint style="info" %}
**For testing only**

n8n designed this kit to help you get started with self-hosted AI workflows. While it’s not fully optimized for production environments, it combines robust components that work well together for proof-of-concept projects. Customize it to meet your needs. Secure and harden it before using in production.
{% endhint %}

[^1]: AI agents are artificial intelligence systems capable of responding to requests, making decisions, and performing real-world tasks for users. They use large language models (LLMs) to interpret user input and make decisions about how to best process requests using the information and resources they have available.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## 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, and the optional `goal` query parameter:

```
GET https://docs.n8n.io/deploy/host-n8n/deploy-with-the-ai-starter-kit.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

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.