Trusted Execution Environments (TEE)

EcoAI integrates Trusted Execution Environments (TEEs) as a secure computation layer for privacy-sensitive inference tasks. In a decentralized system where transparency is paramount, TEE integration introduces a critical exception: zones of encrypted execution, isolated from both public validators and external observers.

When a user activates privacy mode, selected queries and memory calls are routed into TEE-secured nodes. Within these enclaves — implemented via Intel SGX or AMD SEV — the system decrypts context, performs inference, and re-encrypts the response, all without exposing plaintext data at any point. This enables secure use of personal health records, financial insights, or identity-linked logic without violating trust or transparency principles.

TEE in EcoAI is not a bolt-on privacy patch. It is a coordinated runtime extension, synchronized with memory access protocols and agent logic, ensuring that every encrypted task maintains contextual continuity, permission boundaries, and audit traceability. Enclaves are attested and verified, and results carry metadata proofs to confirm execution integrity.

In doing so, EcoAI creates a secure compute layer that matches the composability and modularity of the broader protocol — enabling confidential AI without compromising agent interoperability or user control.