> For the complete documentation index, see [llms.txt](https://kvants.gitbook.io/kvants-whitepaper/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-whitepaper/kvants-studio-the-quantitative-ai-trading-agent-creator.md).

# Kvants Studio: The Quantitative AI Trading Agent Creator

A self-directed software studio for building quantitative AI trading agents from transparent models, validation, education, and export tooling.

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This document describes software. It is provided for informational purposes only. Nothing in it is investment advice, a recommendation, an offer, or a solicitation of any kind. It is not a crypto-asset white paper within the meaning of Regulation (EU) 2023/1114 (MiCA). Trading involves substantial risk of loss. Software features are described as of the publication date and may change, and availability of specific features depends on your jurisdiction. You are responsible for determining whether your use is lawful where you live and where you trade. This document is a product and technology description. It is not a crypto-asset white paper within the meaning of Regulation (EU) 2023/1114 (MiCA), it is not an offer to the public of any crypto-asset, and it is not a solicitation to acquire KVAI or any other token.
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Kvants Studio is the Quantitative AI Trading Agent Creator. The studio exists for users who want their AI agents to reason from quantitative structure instead of reacting only to headlines, chat sentiment, or isolated market events.

The product boundary is direct: Kvants provides research software, graph authoring, signal libraries, backtesting, education, AI assistance, and export tooling. The user authors the strategy, chooses the assumptions, reviews the validation evidence, and controls any execution path outside Kvants.

The four operating surfaces are Build the Model, Operate the Model, The Arena, and The Economy. Build turns ideas into editable strategy graphs. Operate frames terminals, paper workflows, exports, and user-owned execution. The Arena covers simulation-based sharing and learning loops. The Economy explains KVAI as the usage token for metered AI compute.

KVAI is described in this document only as a consumption token used to meter access to AI compute inside the platform. It is not described as equity, debt, revenue share, governance over business proceeds, or a reason to expect platform-driven price outcomes.

## Screenshot

![Kvants Studio: The Quantitative AI Trading Agent Creator](https://raw.githubusercontent.com/KvantsPlatform/kvants-whitepaper-assets/main/assets/landing.png)

*Kvants Studio homepage, cropped to the product identity and navigation surface.*