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Cloak AI — Privacy-First On-Device AI Assistant

Revolutionary local AI companion executing state-of-the-art quantized language models directly on mobile silicon with zero cloud transmission and total data confidentiality.

Live Production Links
0 Bytes Sent Data Telemetry
100% Offline Execution
On-Device NPU Inference Engine
Architecture & Tech Stack:
Android / KotlinJetpack ComposeLocal On-Device LLMs (GGUF / ONNX)Hardware NPU / GPU AccelerationLocal Vector DBTypeScript / Astro Web

Product Overview

Cloak AI is an innovative privacy-first mobile AI assistant created by Androix Limited. Unlike conventional chatbots that transmit user conversations to third-party cloud infrastructure, Cloak AI executes quantized neural weights directly on the device’s neural processing unit (NPU) and GPU.

Accompanied by our web intelligence portal at gomyai.uk, Cloak AI demonstrates our capability in edge artificial intelligence and local machine learning engineering.

┌──────────────────────────────────────────────────────────┐
│                   CLOAK AI ARCHITECTURE                  │
│   Android App (Google Play)       Web Portal (GoMyAI.uk) │
└─────────────────────────────┬────────────────────────────┘


┌──────────────────────────────────────────────────────────┐
│             AIR-GAPPED LOCAL INFERENCE CORE              │
│  ├── Quantized Mobile Neural Weights (4-bit INT4/AWQ)    │
│  ├── Native NPU / GPU Hardware Acceleration              │
│  ├── Local Encrypted SQLite Vector Store                 │
│  └── Zero Cloud Network Dependency                       │
└──────────────────────────────────────────────────────────┘

Key Capabilities

1. Air-Gapped Intelligence

Cloak AI processes complex prompts, document summaries, translations, and technical questions completely offline. Airplane mode, remote travel, or strict corporate data quarantine policies are fully supported.

2. Mobile NPU & GPU Optimization

By leveraging 4-bit quantization and native hardware acceleration layers, Cloak AI delivers rapid token generation with minimal battery draw and thermal throttling.

3. Local Knowledge Retrieval

Users can feed local text notes and documents into a local on-device vector index, enabling accurate semantic question answering without exposing private records.


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