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

# Introducing Opentroy

<figure><img src="/files/x4lB4B3GQze0uOsrMZRC" alt=""><figcaption></figcaption></figure>

Opentroy is a free and open-source platform, designed specifically for artificial intelligence, that runs on your computer. Unlocking the power of local and distributed large language models (LLMs), this system enables you to create powerful AI agents without requiring any coding knowledge.

Thanks to its intuitive interface, you can define tasks, schedule operations, and even have these agents write custom code. Opentroy allows you to automate your business processes and increase your efficiency, all without getting bogged down in technical details.

With native cryptocurrency support, you can also easily manage blockchain-based transactions. Opentroy is a powerful and accessible solution to accelerate your digital transformation and lighten your workload.


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# 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.opentroy.org/welcome-to-opentroy/introducing-opentroy.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.