> For the complete documentation index, see [llms.txt](https://griffin-ai.gitbook.io/knowledge-base/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://griffin-ai.gitbook.io/knowledge-base/decentralized-ai-network/network-design-and-functionality/data-handling-and-system-integrity.md). # Data Handling and System Integrity While the peer-to-peer network is pivotal for the internal functioning and integrity of the system, actual data requests between users and AI models typically occur over standard networks. This approach has been chosen to ensure data concealment and optimization of network performance. Service providers may define custom API endpoints and advertise these over the Griffin service registry. Clients then send their requests directly to these endpoints. Meanwhile, crucial functions such as authentication, authorization, usage tracking, and reputational assessments are managed via the peer-to-peer network and recorded in the distributed database. This dual-network approach not only maximizes the efficiency and security of the network but also maintains the high performance and scalability required by modern AI applications. Through this design, Griffin AI ensures that its ecosystem supports high availability and robust service delivery while safeguarding user data and system integrity. --- # 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://griffin-ai.gitbook.io/knowledge-base/decentralized-ai-network/network-design-and-functionality/data-handling-and-system-integrity.md?ask=&goal= ``` `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.