PastToFutureReverbs A.I. Vinyl Record Plugin Extension

Introducing the world's first AI machine learning audio plugin extension that lets you experience the warmth and richness of vinyl records like never before in the digital domain.

With this revolutionary technology, you can now enjoy the authentic sound of vinyl records, complete with the subtle nuances and imperfections that make vinyl records so unique.

Our AI machine learning audio plugin extension has been designed to accurately simulate the sound of vinyl records by modeling the behavior of the vinyl and the needle. This means you'll hear the distinctive phase distortion which is Vinyl records are known for, as well as the subtle analog distortions that occur when the needle moves across the grooves.

AI was trained for months to achieve these results

What's more, our plugin extension allows you to control the level of these imperfections, so you can dial in just the right amount of warmth and character for your music.

When the included vinyl sample crackle/hiss noise is added, the result is remarkably close to the authentic vinyl sound.

Whether you're a professional producer, a DJ, sound designer, beat maker or just an avid music lover, our AI machine learning audio plugin extension is the perfect tool for adding that classic vinyl sound to your recordings.

The ultimate solution for those seeking to capture the warmth and character of analog devices like tape recorders, tube amps, and guitar pedals in their digital audio recordings.

This cutting-edge technology uses AI machine learning neural networks to create non-linear impulse responses that accurately replicate the sound of analog devices, which normal impulse responses cannot do.

This technology goes beyond traditional impulse responses, providing a more realistic and dynamic sound that truly captures the essence of analog devices.

You will only need to get the free plugin (NAM) that lets you use these AI machine learning non-linear impulse responses.

Simply download the plugin (NAM) from: