Enklayve

100% Local, Always Free, AI-Powered Document Analysis

Enklayve is a secure, privacy-first desktop application that lets you chat with your documents using powerful AI models running entirely on your computer. No cloud services, no subscriptions, no data leaks.

Why Enklayve?

• 100% Local Processing: Everything runs on your device. No internet required.
• Always Free: No subscriptions, no hidden costs, no premium tiers.
• Private by Default: Your documents never leave your computer.
• Powerful Models: Run models like Qwen 2.5, Llama 3.2, Mistral locally.
• GPU Accelerated: Automatic optimization for Apple Silicon and NVIDIA GPUs.

Key Features

Privacy & Security

• End-to-end encryption with AES-256-GCM
• Biometric authentication (Touch ID / Windows Hello / Linux Fingerprint)
• Zero-knowledge architecture
• All data stays on your device

Document Intelligence

• Upload PDFs, DOCX, TXT, Markdown, Excel files
• Ask questions about your documents
• Get answers with source citations
• Vector search for relevant context

Performance

• Hardware-aware model recommendations
• Automatic GPU acceleration (Metal, CUDA)
• Intelligent context window optimization
• Fast embedding generation

User Experience

• Simple mode for beginners
• Advanced mode for power users
• Conversation history
• Export conversations with sources
• Automatic backup and restore

System Requirements

Minimum

• RAM: 8GB (can run 3B models)
• Storage: 10GB available space
• OS: macOS 10.15+, Windows 10+, Ubuntu 20.04+

Recommended

• RAM: 16GB (can run 7B models smoothly)
• GPU: Apple Silicon M1+ or NVIDIA GTX 1060+
• Storage: 50GB available space

For 14B+ Models

• RAM: 32GB+
• GPU: Apple M2 Pro/Max or NVIDIA RTX 3060+
• Storage: 100GB available space

Installation

macOS (Apple Silicon & Intel)

1. Download the DMG installer from Releases
2. Open the DMG file
3. Drag Enklayve to Applications folder
4. Run the following command to allow unsigned app:

   xattr -cr /Applications/enklayve.app

5. Launch Enklayve from Applications

Windows

1. Download the EXE installer from Releases
2. Run the installer
3. Follow the installation wizard
4. Launch Enklayve from Start Menu

Linux

1. Download the AppImage from Releases
2. Make it executable:

   chmod +x enklayve-*.AppImage

3. Run the AppImage:

   ./enklayve-*.AppImage

Quick Start

1. First Launch: Enklayve will detect your hardware and recommend the best model
2. Download Model: Click "Download Recommended Model" (one-time download, 1-20GB depending on model)
3. Upload Document: Drag and drop a PDF or document file
4. Ask Questions: Start chatting about your document
5. Get Answers: Receive intelligent responses with source citations

Supported Document Formats

• PDF (with OCR support for scanned documents)
• Microsoft Word (.docx)
• Plain Text (.txt)
• Markdown (.md)
• Excel (.xlsx, .xls)
• CSV (.csv)

Available Models

Enklayve automatically recommends the best model based on your RAM:

RAM	Recommended Model	Size	Performance
8GB	Qwen 2.5 3B	1.9GB	Fast, efficient
16GB	Qwen 2.5 7B	4.4GB	Balanced, recommended
32GB	Qwen 2.5 14B	8.7GB	Very smart
64GB+	Qwen 2.5 32B	19GB	Maximum intelligence

All models support 32K context window and run at 30-60 tokens/sec on modern hardware.

Building from Source

Prerequisites

• Node.js 20+
• Rust 1.70+
• Platform-specific tools:
  • macOS: Xcode Command Line Tools
  • Windows: Visual Studio Build Tools
  • Linux: GCC, libwebkit2gtk-4.1-dev

Build Steps

# Clone repository
git clone https://github.com/user/enklayve-dev.git
cd enklayve-dev/enklayve-app

# Install dependencies
npm install

# Run in development mode
npm run tauri dev

# Build for production
npm run tauri build

Build Outputs

• macOS: src-tauri/target/release/bundle/dmg/
• Windows: src-tauri/target/release/bundle/nsis/
• Linux: src-tauri/target/release/bundle/appimage/

Project Structure

enklayve-dev/
├── enklayve-app/          # Main Tauri application
│   ├── src/               # React frontend
│   │   ├── components/    # UI components
│   │   ├── App.tsx       # Main app component
│   │   └── main.tsx      # Entry point
│   ├── src-tauri/        # Rust backend
│   │   ├── src/
│   │   │   ├── commands.rs        # Tauri commands
│   │   │   ├── inference.rs       # LLM inference
│   │   │   ├── documents.rs       # Document processing
│   │   │   ├── embeddings.rs      # Vector embeddings
│   │   │   ├── hardware.rs        # GPU detection
│   │   │   ├── encryption.rs      # AES-256-GCM encryption
│   │   │   ├── biometric.rs       # Touch ID / Windows Hello / fprintd
│   │   │   ├── conversations.rs   # Chat history
│   │   │   ├── backup.rs          # Backup/restore
│   │   │   ├── export.rs          # Export functionality
│   │   │   └── model_cache.rs     # Model caching
│   │   └── Cargo.toml    # Rust dependencies
│   └── package.json      # Node dependencies
├── .github/
│   └── workflows/        # CI/CD pipelines
└── README.md            # This file

Architecture

Technology Stack

• Frontend: React 19 + TypeScript + Vite
• Backend: Rust + Tauri 2.0
• LLM Engine: llama.cpp (via llama-cpp-2)
• Embeddings: BGE-Small-EN-v1.5 (fastembed)
• Database: SQLite with encryption
• Vector Search: Custom cosine similarity
• Document Processing: pdf-extract, docx-rs, calamine (Excel), ocrs (OCR)

GPU Acceleration

Apple Silicon (Automatic)

• Metal acceleration enabled by default
• Unified memory architecture for efficient GPU offloading
• Optimized layer distribution based on available RAM

NVIDIA GPUs (Windows/Linux)

• Automatic CUDA detection
• Dynamic GPU layer allocation
• Build with: cargo build --release --features cuda

Troubleshooting

macOS: "App can't be opened because the developer cannot be verified"

Run this command to remove quarantine attribute:

xattr -r -d com.apple.quarantine /Applications/enklayve.app

Model download is slow

Models are large (1-20GB). Download times depend on your internet speed. Downloads can be resumed if interrupted.

Out of memory during inference

Try a smaller model. Qwen 2.5 3B works well on 8GB RAM systems.

App crashes on startup

Check system requirements. Ensure you have at least 8GB RAM and 10GB free disk space.

GPU not detected

• NVIDIA: Install latest drivers and CUDA toolkit
• Apple: Metal is automatic on M1/M2/M3/M4 chips

Linux: Fingerprint authentication not working

Ensure fprintd is installed and fingerprints are enrolled:

# Install fprintd
sudo apt install fprintd

# Enroll fingerprint
fprintd-enroll

Privacy & Security

Enklayve is built with privacy as the foundation:

• No telemetry: We don't collect any usage data
• No analytics: No tracking, no crash reports (unless you opt-in)
• No network calls: Models run 100% offline
• Encrypted storage: All data encrypted with AES-256-GCM
• Secure credentials: Platform keychain integration (macOS Keychain, Windows Credential Manager, Linux Secret Service)
• Biometric unlock: Touch ID, Windows Hello, and Linux fingerprint (fprintd) support
• Open source: Full transparency, audit the code yourself

Performance Tips

1. Use Simple Mode: Advanced mode loads all features, Simple mode is faster
2. Enable Auto-tuning: Let Enklayve optimize settings for your hardware
3. Smaller Context Window: Reduce context window if experiencing slowdowns
4. Close Other Apps: Free up RAM for better performance
5. Use SSD: Store models on SSD for faster loading

Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

License

MIT License - see LICENSE for details.

Support

• Issues: GitHub Issues
• Discussions: GitHub Discussions
• Documentation: docs/

Roadmap

• Image analysis
• Voice input/output
• Multiple document comparison
• Plugin system
• Mobile apps (iOS, Android)

Acknowledgments

Built with:

• Tauri - Desktop app framework
• llama.cpp - LLM inference engine
• Qwen - State-of-the-art language models
• fastembed - Fast embeddings

---

Made with care for privacy and local-first computing.