> For the complete documentation index, see [llms.txt](https://kvants.gitbook.io/kvants-ai-agent/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://kvants.gitbook.io/kvants-ai-agent/ai-agent-governed-quantitative-hedge-fund.md).

# AI Agent Governed Quantitative Hedge Fund

AI has been widely adopted in the technical factor models of quant strategies, with multiple machine learning algorithms and neural networks the analysis of large data sets has never been more effective and efficient. Kvants is at the forefront of providing our investors with access to robust quantitative models that enable risk-adjusted exposure to the digital assets market. 

<figure><img src="/files/Raqwbq4b6Hhx0dZXYhZq" alt=""><figcaption></figcaption></figure>

By introducing our aiQuant.fund an on-chain multistrategy quant fund governed by a framework of AI Agents specialized and trained to deploy into multistrategy Quant Vaults. Each Quant Vault consists of component Quant Strategies, the AI Agents actively rebalance between numerous quant strategies to optimize the performance of the fund.&#x20;

The aiQuant.fund investment platform offers a variety of AI Agent Governed Quant Vaults to invest into, with the interpretation of individual trading decisions being analyzed in real-time, the trade execution framework is entirely at the discretion of our proprietary AI Agents, or as we call them Kvants. Each Kvant Agent has a unique role on the AI Agent Team, we have five main AI agents deployed on the Governance level, and another 300+ independent agents at the strategy level, creating a universe of multiple AI models to produce alpha returns.&#x20;

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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://kvants.gitbook.io/kvants-ai-agent/ai-agent-governed-quantitative-hedge-fund.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
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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.