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 Gryphon 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, Gryphon AI ensures that its ecosystem supports high availability and robust service delivery while safeguarding user data and system integrity.