About Neural Analog
What We Do
We turn your music into actual releases. You have hundreds of tracks sitting idle somewhere. We give you the tools to finish them.
Extract stems with a simple prompt. Restore that compressed MP3 to pristine 20kHz WAV. Master it for Spotify. This is what GPU-enabled music production should look like.
- Stop prompting. Start producing. Upload your AI track and get clean stems and samples that drop straight into your DAW. No artifacts. No ghost frequencies.
- Fix the AI sound. AI audio is full of mud and missing frequencies. Our restoration engine cleans it up and makes it radio-ready.
- Finish the damn song. Sound like a pro with mastering. We bridge the gap between AI generation and professional production.
Who We Are
Hi, I'm Nicov, the creator of this website. I'm an AI engineer and I've been a musician for 10+ years. I've built Neural Analog to help me salvage my old recordings and push the limit of what computers can do with audio.
My goal is simple: bring more beauty to the world. I'm always looking out for new research, techniques, and models to chisel your productions quality with intuitive, performant tools. Join Discord to follow my journey.
The name Neural Analog is inspired from the first neural network built by scientists in 1951, the SNARC. It was analog, not digital. It used continuous electrical signals to learn like a brain.
SNARC learned to navigate a maze like a rat. That was the moment machines proved they could learn from experience. This is the experimental mindset I'm bringing to music production.
Where We Go
The future is analog AI hardware. We want to build for analog neural networks that run audio workflows 1000x more efficiently.
Sub-millisecond latency. Complex models running on dedicated analog chips. MIT, IBM, and Intel are already experimenting there. We want to bring it to audio synthesis.
From your brain to sounds, in a glimpse.