> For the complete documentation index, see [llms.txt](https://pwt-ai.gitbook.io/pwt.ai-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://pwt-ai.gitbook.io/pwt.ai-docs/5.-project-foundation-and-growth-data.md).

# 5. Project Foundation and Growth Data

#### 51｜How many active wallets does PWT.AI currently have?

PWT.AI has established 200K+ active wallets (AUW).

#### 52｜How many users participate in content co-building?

More than 200K users have registered and participated in content co-building.

#### 53｜How many on-chain content interactions have been recorded?

Permacast has recorded 2.65M+ on-chain content interactions.

#### 54｜Can these on-chain interactions be verified?

Relevant Boost content interactions are recorded by smart contracts and can be queried and verified through public blockchain explorers.

#### 55｜What is the global community size of Permacast?

The Permacast X account has established a global community base with nearly 40K followers.

#### 56｜How many people have participated in ecosystem activities?

Through ecosystem activities such as Galxe Quest and Starboard, Permacast has attracted more than 100K participants.

#### 57｜How much cumulative funding has PWT.AI raised?

The project has completed cumulative financing of $8.9M.

#### 58｜Which institutions have invested in or supported the project?

Relevant institutions include OKX Ventures, Big Brain Holdings, Foresight Research, ChainVision, Cipholio Ventures, 7 O’Clock Capital, SilverFox Foundation, CoinSummer, Scorpio VC and others.

#### 59｜Has the project received industry platform recognition?

Permacast has received attention from OKX Ventures and has been listed on RootData. Its financing progress has also been covered by industry media such as ChainCatcher.

#### 60｜What technical research achievements does PWT.AI have?

The project has accumulated ten research achievements covering blockchain edge intelligence, distributed machine learning, data quality, model selection, multimodal collaboration and efficient inference.

#### 61｜Which technical fields do these research achievements mainly cover?

They mainly cover:

* Blockchain and edge intelligence
* Distributed machine learning
* Data quality evaluation
* Blockchain data valuation
* Multimodal semantic consistency
* Agent network scheduling
* Collaborative inference and learning

#### 62｜What value do these research achievements provide?

These research achievements provide theoretical and technical support for intelligent storage, trusted data, distributed model training, algorithm scheduling and multimodal collaboration.

#### 63｜What are the current foundations for PWT.AI’s large-scale development?

Scientific research technology + capital support + user base + on-chain data

These four dimensions jointly form the foundation for PWT.AI to further expand its products, nodes and application ecosystem.


---

# 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://pwt-ai.gitbook.io/pwt.ai-docs/5.-project-foundation-and-growth-data.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.