Skip to content
Need help? Talk to an expert on 0151 236 7800 🚚 Free next-day delivery on UK mainland orders over £99
Need help? Talk to an expert on 0151 236 7800 🚚 Free next-day delivery on UK mainland orders over £99

Waves Key Detector - AI Musical Key Detection Plugin

by Waves
Save 67% Save 67%
Original price £72.00
Original price £72.00 - Original price £72.00
Original price £72.00
Current price
£24.00 inc. VAT
£24.00 - £24.00
Current price
£24.00 inc. VAT
ex. VAT
SKU SWAVKEYDETECTOR
Instant Digital Delivery - All digital sales are final – No refunds.
Please contact us if you are unsure of what to order.

Waves Key Detector - AI Musical Key Detection Plugin

Waves Key Detector finds the key of any sample, track or full mix using Waves' neural networks engine. It gives you the root note, whether the scale is major or minor, and two likely alternatives, even when the material is slightly out of tune.

It also works hand in hand with Waves' vocal tools. Click Transmit and the detected key is sent to every active instance of Waves Tune Real-Time, Waves Tune, Waves Harmony and OVox, saving time on every session.

  • AI-powered key detection with Waves Neural Networks
  • Root note, major or minor scale and two alternatives
  • Analyses full mixes and multi-instrument samples
  • Detects the key even when the pitch is off
  • Transmits the key to Waves Tune, Tune Real-Time, Harmony and OVox
  • Quick and intuitive to use

Supplied as a digital download with a perpetual licence. After purchase you receive a Waves serial number to register to your Waves account; the plugins are then installed and activated with the free Waves Central application, either to your computer or to an exFAT-formatted USB flash drive, one device at a time. A Waves account and an internet connection are needed to activate; no hardware dongle is required. Formats: AAX Native, AudioSuite, AU and VST3 (64-bit) on macOS Sonoma 14 or later, and AAX Native, AudioSuite and VST3 (64-bit) on Windows 10 (64-bit) or Windows 11. Intel and Apple silicon Macs and x64 Intel or AMD PCs are supported; 16 GB RAM is recommended.