Stem organization for producers and mix engineers

Drop in your exported stems. Get back a folder that makes sense.

StemStash classifies instrument type, detects BPM and key, flags silent takes, and groups hundreds of exported stems into DRUMS, BASS, MELODY, VOCALS, and FX with a MASTER BUS reference, so the files land in your DAW already organized.

Up to 0

files per project

0

analysis stages

0h

storage retention

0

generative calls per stem

Deterministic by design

The same set of stems returns the same classification, BPM, and key on every run. Nothing here is a random guess that changes if you re-upload.

You stay in control

Every detected group, filename, BPM, and key is editable in a review table, with a visible confidence score, before anything exports.

Built for volume

Drag in tens or hundreds of files at once, with resumable uploads and per-file progress.

Interactive preview

See it in action

The same six stems, before and after. Nothing here is uploaded or processed. This is a click-through preview of the real export structure.

Before

  • kick (3) FINAL_v2.wav
  • New Recording 14.wav
  • Untitled-1.wav
  • vocal_take_9_use this one.wav
  • audio_export_bounce_2am.wav
  • Master_v7_ACTUALFINAL.wav

After

Click “Clean up” to preview the organized output.

How the analysis pipeline works

5 stages, per project

01

Classification

Zero-shot audio classification

Each stem is scored against dozens of instrument and sound categories. Long files are split into consecutive windows and analyzed as a whole, not a single random slice, so the same file returns the same label every time it runs.

02

Tempo

Onset-based beat tracking, project-wide consensus

Rather than trusting one stem's guess, tempo is built from consensus across every rhythmic file in the project. Drum and bass content is weighted higher, and half-time or double-time reads are folded into a single stable BPM.

03

Key

Chroma pitch-class correlation

Key detection correlates chroma energy against major and minor key profiles using the Krumhansl-Schmuckler method. Percussion, FX, and silent stems are excluded from the project-level consensus, so a kick drum never skews the result.

04

Master detection

Evidence-based, never volume alone

The master bus is identified from filename signal, classification confidence, and duration together. The loudest file in a session is never assumed to be the master.

05

Silence

Peak-based level analysis

Empty takes are flagged from peak level across the full file, not an average. A track with a few sparse hits in an otherwise quiet file is not mistaken for silence.

Output groups

DRUMSBASSMELODYVOCALSFXMASTER

Specification

Input formats
WAV, AIFF, FLAC, MP3
Files per project
Up to 500
Max file size
50 MB
Storage retention
Up to 24 hours after export
Analysis
Deterministic, no per-stem generative call