Can AI replace Krisp?

Build me a noise-cleanup tool to replace Krisp for recordings, not live calls. Requirements:

- Be honest in the README up front: real-time suppression as a virtual microphone
  needs an OS-level audio driver and millisecond latency. That is Krisp's actual
  product and it is out of scope here. This tool cleans audio files after the fact.
- A CLI: `denoise in.wav` (mp3/m4a accepted, decoded via ffmpeg) writes
  in.clean.wav next to the original, original untouched.
- Use RNNoise for the suppression pass (ffmpeg's arnndn filter with a downloaded
  model file is the easy route), then a loudnorm pass so voice levels come out
  consistent.
- A watch mode with chokidar: drop files into ~/Denoise/in/ and cleaned versions
  appear in ~/Denoise/out/ with the same names.
- Batch mode for whole folders, with a printed before/after noise estimate per file.
- Node wrapping ffmpeg, or a plain bash script if that ships simpler. No server,
  no GUI.
- Fully local and offline: no accounts, no telemetry, no API calls.
- Out of scope: live call processing and a virtual audio device. For live calls the
  README should point me at the OS's built-in voice isolation instead.
- README: ffmpeg and RNNoise model install, one-line usage examples.