AudioKeep is a world-class AI-powered audio restoration and enhancement platform designed for professionals in archival preservation, audio forensics, broadcast restoration, and historical audio digitization.
- Advanced noise reduction (background noise, hiss, hum, buzz)
- Click and pop removal (vinyl/tape damage)
- Spectral repair for damaged audio sections
- Declipping for distorted audio restoration
- Electrical interference removal (50/60Hz hum)
- AI-powered speech enhancement
- Audio super-resolution (upsample to 48kHz/96kHz/192kHz)
- Voice isolation and source separation
- Bandwidth extension
- Dynamic range enhancement
- Audio forensics tools for law enforcement
- Detailed spectral analysis
- Authentication and tampering detection
- Forensic reporting
- Batch processing capabilities
- Real-time A/B comparison player
- Waveform and spectrogram visualization
- Credit-based pricing model
- Multiple quality tiers
- API access for enterprise
- FastAPI - Modern Python web framework
- PyTorch - AI model inference
- Celery - Distributed task queue
- PostgreSQL - Primary database
- Redis - Queue and caching
- MinIO/S3 - File storage
- React 18+ with TypeScript
- Vite - Build tool
- TailwindCSS - Styling
- Shadcn/ui - Component library
- React Query - Data fetching
- Zustand - State management
- Wavesurfer.js - Audio visualization
- Resemble Enhance - Speech denoising and enhancement
- AudioSR - Audio super-resolution
- DeepFilterNet - Advanced noise reduction
- Demucs v4 - Source separation
- FlashSR - Fast super-resolution
- 8GB+ RAM
- 4+ CPU cores
- 10GB disk space
- GPU: NVIDIA RTX 6000 Ada (48GB VRAM)
- CPU: AMD EPYC 9354 (32 cores, 64 threads)
- RAM: 128GB
- Storage: 1TB NVMe SSD
- Docker and Docker Compose
- Node.js 18+ (for frontend development)
- Python 3.11+ (for backend development)
- NVIDIA GPU with CUDA 12.x (for production)
- Clone the repository
git clone https://github.com/yourusername/audiokeep.git
cd audiokeep- Set up environment variables
cp .env.example .env
# Edit .env with your configuration- Start development environment
docker-compose -f docker-compose.dev.yml up- Access the application
- Frontend: http://localhost:5173
- Backend API: http://localhost:8000
- API Documentation: http://localhost:8000/docs
See DEPLOYMENT.md for detailed production deployment instructions.
audiokeep/
├── backend/
│ ├── app/
│ │ ├── api/v1/endpoints/ # API route handlers
│ │ ├── core/ # Core configuration
│ │ ├── models/ # Database models
│ │ ├── schemas/ # Pydantic schemas
│ │ ├── services/ # Business logic
│ │ ├── ai_models/ # AI model integrations
│ │ └── db/ # Database utilities
│ ├── tests/ # Backend tests
│ └── requirements.txt
├── frontend/
│ ├── src/
│ │ ├── components/ # React components
│ │ ├── pages/ # Page components
│ │ ├── hooks/ # Custom React hooks
│ │ ├── services/ # API services
│ │ ├── store/ # State management
│ │ └── types/ # TypeScript types
│ ├── public/ # Static assets
│ └── package.json
├── deployment/
│ ├── docker/ # Dockerfiles
│ └── kubernetes/ # K8s manifests
├── docs/ # Documentation
├── scripts/ # Utility scripts
├── ARCHITECTURE.md # System architecture
└── docker-compose.yml
Once the backend is running, visit http://localhost:8000/docs for interactive API documentation (Swagger UI).
AudioKeep uses a credit-based pricing model:
- 50 credits on signup
- Standard quality processing
- Max 100MB file size
- Max 30 minutes duration
- Starter: 100 credits - $9.99
- Professional: 500 credits - $39.99
- Studio: 1,500 credits - $99.99
- Enterprise: 5,000 credits - $299.99
- Pro: $29.99/month (500 credits)
- Studio: $79.99/month (1,500 credits)
- Forensic: $199.99/month (4,000 credits + forensic tools)
- 1-minute podcast cleanup: ~2 credits
- 10-minute interview restoration: ~35 credits
- 60-minute archival tape (ultra quality): ~240 credits
- 5-minute forensic analysis: ~30 credits
cd backend
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
pip install -r requirements.txt
uvicorn app.main:app --reload --host 0.0.0.0 --port 8000cd frontend
npm install
npm run dev# Backend tests
cd backend
pytest
# Frontend tests
cd frontend
npm testWe welcome contributions! Please see CONTRIBUTING.md for guidelines.
Copyright (c) 2025 AudioKeep. All rights reserved.
This is proprietary software. See LICENSE.md for details.
- Documentation: https://docs.audiokeep.io
- Email: support@audiokeep.io
- Issue Tracker: https://github.com/yourusername/audiokeep/issues
- Core audio processing features
- User authentication and credits system
- Basic UI with upload/download
- Stripe payment integration
- Subscription tiers
- Batch processing
- Advanced visualizations
- Email notifications
- Forensic analysis tools
- API for enterprise
- Team accounts
- Priority processing queue
- Mobile applications
- DAW plugin integrations
- White-label solutions
- Advanced analytics
AudioKeep Development Team
- Resemble AI for Resemble Enhance
- Meta/Facebook Research for Demucs
- Open-source audio processing community
- All contributors and testers
Built with ❤️ for audio preservation professionals worldwide