📄️ MEV
This is a public resource for learning about Trusted Execution Environments (TEEs). Our aim is to provide comprehensive coverage of key concepts, research advancements, and real-world applications of TEEs.
📄️ Confidential chains
This is a public resource for learning about Trusted Execution Environments (TEEs). Our aim is to provide comprehensive coverage of key concepts, research advancements, and real-world applications of TEEs.
📄️ TEE Coprocessors
This is a public resource for learning about Trusted Execution Environments (TEEs). Our aim is to provide comprehensive coverage of key concepts, research advancements, and real-world applications of TEEs.
📄️ AI Agents
AI Agents often handle sensitive user data, perform mission-critical tasks and, in some cases, manage user funds. This dual responsibility makes Trusted Execution Environments (TEEs) particularly well-suited for AI Agent applications due to two critical properties:
📄️ MCP Servers
MCP (Model Context Protocol) Servers are specialized services that provide AI models with access to external data sources, tools, and APIs. They act as intermediaries between AI models and various data repositories, enabling models to retrieve real-time information, execute actions, and access contextual data that enhances their capabilities.
📄️ MPC Nodes
MPC (Multi-Party Computation) Nodes are specialized computing nodes that participate in distributed cryptographic protocols where multiple parties jointly compute a function while keeping their individual inputs private. These nodes are essential for applications requiring secure computation across multiple participants without revealing sensitive data to each other.