Secure TEE Computation

Secure TEE Computation is the privacy execution engine of PrivAI — a foundational system that enables complex, high-sensitivity tasks to be performed in a manner that is fully confidential, cryptographically verifiable, and hardware-isolated. At its core is the Trusted Execution Environment (TEE): a physically secure area within a processor that guarantees code and data loaded inside remain invisible and tamper-proof to all external processes — including the host operating system and node administrators.

Unlike standard blockchain executions, where every transaction is public, TEE allows PrivAI to handle private logic and sensitive data without exposing anything to the public ledger. This makes it possible to automate operations like protected DeFi strategies, personal health analytics, or proprietary model inference — all while maintaining regulatory-grade confidentiality.

PrivAI integrates TEE computation using two major infrastructures:

• Phala Network for EVM-compatible environments

• Secret Network for the Solana ecosystem

Whenever a user toggles Privacy Mode, the PrivAI platform securely redirects their task into a TEE-enabled computation pipeline. This process is defined by five distinct steps:

1. Task Encryption & Dispatch: The user’s data, models, and instructions are encrypted client-side and transmitted to a designated TEE node based on their blockchain context (EVM or Solana).

2. Secure Enclave Initialization: The selected node initializes its TEE enclave, ensuring it’s running the correct, authorized AI Agent code. At this stage, a unique enclave ID is created, and integrity is verified using hardware-level cryptographic checks.

3. Confidential Task Execution: Inside the enclave, data is decrypted only within protected memory. The AI Agent performs the full operation — such as computation, analysis, or strategy execution — without ever exposing internal values to the host machine.

4. Remote Attestation: Once complete, the enclave generates a cryptographic attestation proof, signed by the CPU’s root of trust. This attestation includes details such as task metadata, enclave fingerprint, and success verification. The proof is recorded on-chain, offering a public and immutable record that the task was executed securely and honestly.

5. Result Encryption & Return: The output of the task is encrypted again and delivered back to the user or posted to the blockchain, depending on the privacy requirements. In every case, the raw computation remains inaccessible to third parties.

This process transforms how privacy is implemented in decentralized systems — shifting away from vague claims to provable, measurable confidentiality. Importantly, Secure TEE Computation does not rely on user trust in the infrastructure provider or node operator. Instead, it offers mathematical and hardware-level guarantees that the computation was carried out as intended, without interception or modification.

By integrating Secure TEE Computation as a core part of its protocol, PrivAI becomes capable of supporting use cases that conventional dApps cannot handle — such as sealed-bid auctions, confidential governance proposals, biometric AI inference, or encrypted multi-party workflows. This functionality is essential to positioning PrivAI as the go-to infrastructure for AI-powered, privacy-compliant decentralized services.

In PrivAI, privacy is not a theoretical feature or optional setting — it is a verifiable execution standard. Secure TEE Computation ensures that privacy is enforced by the machine, proven by cryptography, and trusted by design.