DeepvBrowser voice-native AI browser logo
DeepvBrowser

Technical Advantages

Cloud LLM × Local Encrypted Acceleration
DeepvBrowser places heavy inference in the cloud while keeping critical information on the device. Local components only handle voice triggering, caching, and fast UI rendering. This enables access to the latest models while maintaining core usability in weak network scenarios.

Four Core Technologies

☁️ Cloud LLM Inference

Dynamic cloud-side LLM calls for real-time access to latest knowledge and reasoning capabilities. CDN-accelerated latency averaging under 300ms.

🔒 AES-256 End-to-End Encryption

Unified AES-256 encryption for device-cloud transmission and local storage. Verified encryption/decryption solution on Flutter.

⚙️ WebAssembly Sandbox

Third-party tools/parsers compiled into WASM modules, running in isolated sandboxes for security

🔄 Hybrid Offline Cache

Voice commands, translation models, and reading content cached locally for offline use

AI Capability Visualization

Content Analysis85% Accuracy

Cloud LLM Comprehensive Evaluation

Personalized Recommendations92% Precision

A/B Testing Feedback

Smart Summary0.5s Avg First Token Time

Hybrid Cache + Streaming Response

Voice Recognition97% Word Error Rate ≤3%

Cloud-Device Collaboration, Weak Network Fallback to Local Engine

Privacy & Compliance

Local Data Priority Storage

Compliant with GDPR / PIPL minimization principles

Device-Cloud Link Encryption

TLS 1.3 + AES-256, Key management via Secure Enclave / Android KeyStore

Private Mode & Smart Anti-Tracking

Block third-party fingerprinting scripts

Technical Architecture

Cloud LLM × Flutter Client, Lightweight Local Plugins
DeepvBrowser uses Flutter cross-platform framework to build the client, with heavy AI inference completed in the cloud. Local components only handle voice triggering, data caching, and UI rendering, achieving the perfect balance between optimal performance and latest model capabilities.

Flutter Cross-Platform Client

Native Performance & Unified Experience

60 FPS+ smooth rendering, unified iOS/Android development

Cloud LLM Cluster

Latest Models & Real-time Inference

Supports multimodal inference, CDN-accelerated global deployment

Lightweight Local Engine

Voice Wake-up & Basic NLP

Offline speech recognition, keyword parsing, weak network backup

WebAssembly Sandbox

Secure Plugin Environment

Third-party tools run in isolation, near-native performance

Intelligent Cache System

Local Data Warehouse & Offline Capabilities

SQLite local storage, smart pre-caching strategy

End-to-End Encryption

TLS 1.3 & AES-256

Hardware key management, secure data transmission

* Data based on Q2 2025 beta testing samples. Device specs: A15 / Tensor G3. Full test report coming soon.

Frequently Asked Questions

Common questions and answers about DeepvBrowser to help you better understand our product

Try It Now

Download DeepvBrowser and start the new era of efficient and intelligent mobile browsing

iOS Version

Supports iOS 12.0+ systems Available on App Store