> For the complete documentation index, see [llms.txt](https://equinoxai.gitbook.io/equinox-ai-whitepaper/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://equinoxai.gitbook.io/equinox-ai-whitepaper/data-brokerage-and-expansion/whitelabelling-and-platform-licensing.md).

# Whitelabelling & Platform Licensing

<figure><img src="/files/ECRIX8SO5OwWqQE18OJ4" alt=""><figcaption></figcaption></figure>

### Equinox AI is structured as a modular intelligence infrastructure with a clear vision: to offer a licensable stack that can integrate across multiple verticals. As part of this roadmap, we also envision Equinox becoming the most comprehensive behavioural data broker in Web3 — offering structured, enriched, and privacy-compliant data to platforms that need actionable intelligence. While not yet available, whitelabelling and licensing are core pillars of this future rollout.

These offerings are being developed for:

* Trading platforms
* Security & compliance dashboards
* Fund analysis tools
* Wallet apps
* DeFi protocols

***

#### Licensing Options (Planned)

| Tier               | Description                                             |
| ------------------ | ------------------------------------------------------- |
| API Access         | Access to raw indexed data (on/off-chain intelligence)  |
| Dashboard Embed    | Custom-branded visual modules for existing products     |
| Full Stack Package | Dedicated instance with hosted backend and UI licensing |

Final licensing terms will include usage-based fees, optional support layers, and tier-based access. Pricing, availability, and documentation will be made public upon rollout.

***

#### Potential Use Cases

* A DEX integrating Equinox AI’s wallet risk scoring engine
* Telegram-based trading tools using our influencer mapping modules
* Research teams embedding behavioural pattern detection in internal dashboards

***

**We aim to evolve into the most trusted and accurate behavioural data provider in Web3. Our future whitelabelling model is designed for extensibility, speed of integration, and modular control — all deployable in secure, independent environments.**


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