DeepFlow: Confidential AI Phone Architecture

Core Capabilities

Edge-Side Privacy

Real-time data desensitization ensuring user data stays private before it leaves the device.

Cloud TEE + NVTrust

Confidential AI inference environments protected by hardware-level isolation.

GUI Agents

Autonomous dApp execution capable of interacting with complex web interfaces.

ZK Verification

Generate cryptographic proofs of action without revealing sensitive underlying data.

Intent Automation

Translate natural language commands into complex multi-step workflows.

Decentralized Compute

Scalable integration with decentralized networks for robust availability.

Industry Revolution

On the eve of AGI, DeepFlow is making a forward-looking strategic layout. By supporting the integration of intent-driven architecture with AI-native blockchain paradigms, DeepFlow is establishing deep collaborations with top exchanges, infrastructure providers, and dApp developers.

The trusted computing solution of Cloud CPU TEE + GPU NVTrust not only solves current privacy pain points but also paves the way for the future Web3 Agentic era. In the AGI era, DeepFlow is committed to embedding trusted computing fully automated AI assistants as the core engine of Web3.

The strategic value of this layout lies in reshaping Web3 traffic logic and leading the industry towards a smarter and safer evolution. DeepFlow is not just a technology provider, but the architect of the Trusted AI era.

Architecture Innovation

DeepFlow creatively proposes a "Cloud-Edge Hybrid Intelligence Architecture," achieving the optimal balance between performance, privacy, and cost. This architecture redefines AI as the intelligent middle layer of Web3, abstracting protocol complexity and providing users with a natural language-driven intent execution interface.

On the edge side, lightweight AI models identify and desensitize all sensitive inputs in real-time on user devices. Raw private data such as private key fragments, transaction passwords, and identity information never leave the user device, ensuring the highest level of local security protection.

More importantly, highly sensitive operations such as key signing and key management are performed in TEE secure enclaves isolated from the main system, providing hardware-level security guarantees.

Technical Moat

DeepFlow's technical moat is built on two core innovations: the Trusted Execution Environment on the edge side and the Trusted Computing solution on the cloud side.

On the cloud side, DeepFlow adopts the industry-leading combination of CPU TEE and GPU NVTrust to build a comprehensive confidential computing framework. CPU TEE creates secure enclaves to ensure code and data are safe from external access during runtime, while GPU NVTrust extends confidential computing to the GPU domain, supporting AI large models to execute inference tasks within protected areas.

The core difference lies in security levels and computing modes. Traditional solutions rely on software encryption, exposing data to risks during computation; while DeepFlow's solution achieves hardware-level isolation protection, ensuring full-link privacy security from edge to cloud.

Aspect	Traditional Solution	DeepFlow Architecture
Privacy Model	Software Encryption (Vulnerable at runtime)	Hardware TEE + NVTrust (Hardware isolation)
Execution Mode	Manual Scripts / Basic Bots	Autonomous AI Agents (Intent-driven)
Trust Mechanism	Centralized Trust	Verifiable ZK Proofs + On-chain Verification
Data Handling	Cloud-based Processing	Edge-Cloud Hybrid (Sensitive data stays on device)

Confidential AI Phone Architecture