> For the complete documentation index, see [llms.txt](https://maximize-ai.gitbook.io/maximize-ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://maximize-ai.gitbook.io/maximize-ai/maxiscreen-visual-dashboard-for-decentralized-ai.md).

# MaxiScreen: Visual Dashboard for Decentralized AI

#### The Transparency Solution

MaxiScreen transforms complex Bittensor network data into intuitive, actionable insights, addressing the opacity of decentralized AI infrastructure.

#### 3.2 Key Features

**Live Subnet Metrics**

* Market Data: Real-time market cap, volume, and TAO emission tracking
* Network Performance: Validator uptime, miner rankings, consensus metrics
* Supply Analytics: TAO and $MAXI token supply economics
* Subnet Health: Overall network stability indicators

**Network Visualization**

* Validator-Miner Dynamics: Interactive graphs showing relationships and scoring
* Consensus Flow: Visual representation of network decision-making
* Reward Distribution: Clear visualization of emission flows
* Hyperparameter Tracking: Real-time network parameter monitoring

**User Interface**

* Intuitive Navigation: Tab-based organization for easy data discovery
* Mobile Optimized: Full-featured mobile interface
* Real-time Updates: Live data streaming with visual indicators
* Customizable Dashboards: User-defined metrics and alerts

#### 3.3 Technical Architecture

* Direct Bittensor Integration: Real-time API connection to network data
* Market Data Feeds: Bittensor integration for pricing and volume
* Global CDN: Scalable hosting with worldwide distribution
* High Performance: Sub-second updates, support for 10,000+ concurrent users


---

# 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://maximize-ai.gitbook.io/maximize-ai/maxiscreen-visual-dashboard-for-decentralized-ai.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.
