> For the complete documentation index, see [llms.txt](https://gata.gitbook.io/gata-public-gitbook/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://gata.gitbook.io/gata-public-gitbook/business-model/markdown.md).

# Revenue Model

## 1. Licensing / Access Fees

Gata charges access fees to AI companies that wish to use our frontier datasets. Tiered licensing can address varying usage scopes (e.g., research, commercial, exclusive).

Datasets suitable for licensing fees include:

* **Over 5.3M Real-User ChatGPT Data**, best human-AI interaction data in the world
* **Over 106k Real-User OpenAI o1 reasoning Data**, helpful for training reasoning AI
* **Human preference data**, critical for human-AI alignment

## 2. (Co-)Development of AI Products

When Gata's unique frontier data establishes a significant competitive advantage for certain AI products, we may co-develop those products with partners or develop our own proprietary AI solutions. Revenue is generated through product sales, subscriptions, or exclusive service offerings. Additionally, we may negotiate royalties or revenue-sharing agreements for the final AI product. This approach ensures that Gata's incentives are directly aligned with the success of the AI products.

Datasets suitable for (co-)development of AI products include:

* Upcoming. Stay excited...


---

# 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://gata.gitbook.io/gata-public-gitbook/business-model/markdown.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.