LALAL.AI

LALAL.AI is a cloud-based audio stem separation platform built around an API-first architecture. It splits mixed audio into isolated stems — vocals, instrumentals, drums, bass, piano, and more — using neural network processing that runs entirely on the vendor's servers. The current API version is 1.1.0, documented through a public OpenAPI 3.1.0 specification with companion code examples available on GitHub.

The platform exposes multiple separation modes through its REST API. The stem separator endpoint extracts a single stem type per request, while the multi-stem endpoint isolates several components in one pass. A batch endpoint handles multiple files simultaneously, and all endpoints support task cancellation and status checking. Voice-clean presets accept a configurable noise-cancelling level parameter, and the Lead & Back Vocal Splitter includes a de-echo toggle designed to clean up vocal stems extracted from tracks with reverb or room ambience.

Authentication uses a license key passed in the X-License-Key header. The standard workflow follows an upload-then-split pattern: users upload a source file to the /upload/ endpoint, receive a source file ID, and then submit that ID to a split endpoint. The API returns task objects for polling, and uploaded files are automatically deleted when the server-defined expiration window closes.

LALAL.AI's business solutions documentation describes an Enterprise tier that lifts restrictions significantly — unlimited processing minutes, 10 GB per-file uploads, API integration, batch upload, and VST plugin support. Lower tiers are capped at 30 minutes and 2 GB per file without API or batch access, according to the vendor's published comparison table. The business page promises throughput for "thousands of minutes" of audio and video and touts seamless deployment into customer environments, though independent throughput benchmarks are not present in the source materials.

A free Starter plan allows file uploads and separation previews but does not include full downloads. Paid plans unlock complete stem downloads. The vendor describes the basic web workflow as requiring "no technical know-how" — the user uploads a track and the AI handles the rest. Supported input formats cover common lossy and lossless audio codecs — MP3, WAV, FLAC, AAC, OGG, AIFF — as well as video containers including MP4, AVI, MKV, MOV, and M4V, giving it broad compatibility for content sourced from video projects.

The vendor attributes its separation quality to the Andromeda audio transformer neural network, described in a proprietary blog post referenced in the source documentation. No independent third-party benchmarks or double-blind listening tests are included in the source pack to validate these performance claims against competing solutions in the AI Noise Cancellation space.

For developers, the API's OpenAPI 3.1.0 compliance enables client generation across languages. The GitHub repository provides Python code examples covering upload, split, and result-fetching workflows, lowering the integration barrier. For musicians and content creators, the web interface eliminates installation overhead — a practical trade-off that exchanges offline capability for zero-setup access.