Fast Restore
Applies light noise reduction and basic band correction to eliminate background hiss and hum in milliseconds. Optimized for speed and low CPU usage. Perfect for bulk initial cleanup.
Professional-grade local audio restoration tool for macOS and Windows to reconstruct damaged spectrums and eliminate extreme noise
Pure Restore is a professional desktop audio restoration app designed for macOS and Windows. Powered by advanced deep learning neural networks, it reconstructs damaged frequency bands for heavily compromised audio and vocal recordings. Whether dealing with clipping, extreme wind noise, or severe ambient distortion, Pure Restore runs 100% locally to recover vocal clarity and original warmth in seconds.
Applies light noise reduction and basic band correction to eliminate background hiss and hum in milliseconds. Optimized for speed and low CPU usage. Perfect for bulk initial cleanup.
Utilizes mid-level neural network models for multiband noise suppression, dereverberation, and vocal clarity compensation. Optimized for natural speech realism. Ideal for podcasts and online classes.
Deploys high-precision deep learning networks for full-spectrum reconstruction of damaged frequency bands, thoroughly eliminating clipping, wind noise, and severe distortion.
All processing runs locally on your Mac or PC. No network connection required, and files never leave your device.
Control the underlying binary directly from Terminal. Customize input/output paths and secure folder access, perfect for automated script pipelines.
No, 100% of the processing is done locally on your Mac or PC. No network access is required, and your files never leave your device.
Pure Restore is built to 'rescue' heavily distorted, noisy, and clipped audio by reconstructing missing frequencies. Pure Refine is designed to 'polish' clean recordings (e.g., adding warmth and presence). Together, they form the ultimate 'Restore First, Refine Next' workflow.
Pro subscribers can invoke the command line tool via Terminal. It supports quiet background executions and is perfect for automation scripts.
You can reach us via email feedback@efficient-lab.com or submit issues and suggestions through GitHub Issues.