> For the complete documentation index, see [llms.txt](https://whitepaper.swe.at/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://whitepaper.swe.at/usdsweat-whitepaper/6.-partnerships-a-movement-powered-by-strategic-collaboration/6.2-near.ai-intelligence-that-scales.md).

# 6.2 NEAR.AI: Intelligence That Scales

SWEAT’s AI Agents are powered by **NEAR.AI**. An innovation layer that brings personalized intelligence into the hands of every user. These agents, trained on over **700,000 real user queries**, guide users through every interaction in Sweat Wallet, explaining features, spotting scams, and recommending actions in real time.

As user volume scales into the tens and hundreds of millions, NEAR.AI ensures that support remains personal, contextual, and human—even at machine speed. It turns **each interaction into insight and action.**

NEAR.AI is turning SWEAT’s digital economy into a smart economy. One where every user has a tailored experience, powered by decentralized intelligence.


---

# 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://whitepaper.swe.at/usdsweat-whitepaper/6.-partnerships-a-movement-powered-by-strategic-collaboration/6.2-near.ai-intelligence-that-scales.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.
