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ACCESS Newswire
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LALAL.AI Expands Its Developer API With AI Multi-Stem Separation & Voice Cloning

Developers can now embed studio-grade stem separation and consent-based voice cloning into their apps.

ZUG, CH / ACCESS Newswire / February 27, 2026 / LALAL.AI , an AI-powered audio processing platform, releases its updated API v1, enabling developers and product teams to plug into production-ready audio AI, instead of training costly audio models.

AI-powered creator tools continue to proliferate, and many startups encounter the same obstacle: building and training high-quality audio models requires significant time, expertise, and infrastructure investment. Increasingly, companies are shifting toward plug-and-play audio AI APIs that allow them to integrate advanced functionality without developing their own models from scratch. In this context, audio AI is moving into production-ready infrastructure for the creator economy rather than remaining an experimental add-on.

LALAL.AI 's API v1 reflects that shift. Delivered with a clear OpenAPI specification and a Swagger-like interface, the API enables developers to explore, test, and validate endpoints before committing to full integration. At the same time, it is designed to handle bulk processing and batch workloads, making it suitable for products operating at scale.

This is what the new API can bring to a product or a creative pipeline:

Audio or video files can be split into stems (vocals, instruments, drums, bass, acoustic and electric guitar, piano, strings and wind instruments) using predefined separator presets.

Background music can be removed from voice recordings.

Unwanted background noise can be eliminated.

Multiple files can be processed in a batch: a single request can now trigger multi-stem separation, isolating vocals, drums, bass, synths, acoustic and electric guitars, piano, strings, wind instruments, as well as voice and background noise.

In addition, API v1 introduces voice transformation through licensed Voice Packs , allowing partners to change the voice in an audio file within a commercially supported framework.

Rather than releasing a collection of isolated endpoints, LALAL.AI positions API v1 as a full-stack audio AI infrastructure layer. "With API v1, we're opening up a full-stack audio AI infrastructure. Developers can now embed multi-stem separation and voice cloning safely, at scale, into their products," says Nik Pogorsky, LALAL.AI Product Owner & Co-founder. "We believe that our technology will open up new possibilities for a new wave of creator tools."

The API is production-ready and available for immediate commercial integration, eliminating the need for additional model training or complex infrastructure overhead.

Previously, LALAL.AI 's API powered integrations with a major video editor that automatically separated vocals and background music, as well as localization platforms that isolated dialogue tracks for multilingual subtitling. According to one localization platform that integrated LALAL.AI, processing time was reduced from prohibitively long to seconds - or just a few minutes for longer content - and quality complaints fell to nearly zero after the adoption of the latest model.

With v1, those established use cases are extended through multi-stem separation and embeddable voice capabilities, broadening the scope for video editors, podcasting platforms, localization services, and other creator-focused platforms.

Voice cloning, in this framework, is no longer presented as a standalone novelty feature but as embeddable infrastructure. All voice-related functionality is developed with consent and licensing considerations in mind, ensuring that integrations respect the rights of content creators and rights holders.

The quality of LALAL.AI 's stem separation has received independent recognition, ranking strongly in the Pro Instrument category of Meta's benchmark and earning a 5/5 rating for vocal and drum separation in an independent MusicRadar review this year.

To learn more about LALAL.AI API, read its documentation and see examples, users are encouraged to visit the company's official website.

Contact Information:

Klara Alexeeva, LALAL.AI Communications Manager
klara.alexeeva@lalal.ai

SOURCE: LALAL.AI



View the original press release on ACCESS Newswire:
https://www.accessnewswire.com/newsroom/en/computers-technology-and-internet/lalal.ai-expands-its-developer-api-with-ai-multi-stem-separation-1141852

© 2026 ACCESS Newswire
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