Resonance Labs today announced the launch of Tensormix, a music mastering online platform that leverages large language models to deliver bespoke, release-ready masters tailored to each individual track. Unlike traditional automated mastering services that rely on preset templates, Tensormix harnesses the audio engineering knowledge embedded in frontier AI models to analyse and master music with the nuance of a PhD-level audio engineer.
Tensormix treats every track as unique, deploying agentic AI systems that make real-time decisions based on the specific characteristics of each audio file. No two mastering jobs are the same, ensuring completely personalised results that respect the artistic intent of the original mix.
A New Philosophy for AI in Music
“We’ve stepped into a new era of AI-powered creation. But the next once-in-a-generation artist won’t emerge by simply prompting their way to brilliance,” said Yan Osovsky, founder of Resonance Labs. “Our mission is to protect what makes music human – by building tools that empower real musicians, not replace them.”
Rather than use frontier AI technologies to generate music from text prompts, Tensormix serves as an intelligent collaborator that enhances work created by human artists. The platform brings professional-grade mastering capabilities to independent musicians and producers.
How Tensormix Works
Tensormix operates as an agentic system with access to professional audio processing tools including equalisers, compressors, limiters, and spatial enhancers. When a user uploads a track, the AI agent analyses the spectral content, dynamic range, stereo field, and tonal balance, then formulates a bespoke mastering strategy tailored to that specific track, applying processing iteratively with real-time adjustments based on measured results.
About Resonance Labs
Resonance Labs is a UK-based audio technology company working to help define how frontier AI technologies should be deployed in music production. The company’s mission is to ensure these powerful tools enhance and support real musicians, preserving human artistry while making professional-grade capabilities accessible to independent artists.
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