> 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 by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://whitepaper.swe.at/usdsweat-whitepaper/6.-partnerships-a-movement-powered-by-strategic-collaboration/6.2-near.ai-intelligence-that-scales.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. 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.