Music That Moves With You

Sound that listens back.

AURNO builds adaptive audio intelligence — real-time sound that responds to motion, biometrics, and human performance.

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Our Vision

Music has always moved us. But never with us.

For decades, sound has been static — recorded moments replayed the same way, regardless of who we are, how we feel, or what our bodies are doing. Meanwhile, every other part of our world has become intelligent, responsive, and alive with data. We believe music should evolve too.

AURNO exists to transform sound from something you listen to into something that listens back. This is not about playlists. It's about a living soundtrack — continuously shaped by who you are and what you're doing. Because when music can keep up with you, there's no limit to where you can go.

The Science

Music isn't background.
It's infrastructure.

Two decades of peer-reviewed research point in one direction: music doesn't just accompany exercise — it measurably changes outcomes.

"Music is a legal performance-enhancing drug."
— Karageorghis & Priest, International Review of Sport & Exercise Psychology
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Effect size on workout enjoyment — the largest measured impact of any exercise intervention studied, across an 18-study meta-analysis.
↓ RPE
Perceived exertion reliably falls when music is present — increasing work output during endurance tasks without increasing perceived effort.
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Users preferred adaptive music over standard playback in a controlled trial — with transitions perceptually indistinguishable from unmodified audio.

Sources: Danso et al., JMIR Human Factors (2025) · Karageorghis & Priest (2012) · Montecchio, Roy & Pachet, PLOS ONE (2020) · Wang, Donahue & Jain, ISMIR (2025)

The Market

Music is the hidden driver.

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of people listen to music while working out.
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monthly active users globally across major fitness platforms.
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annual music streams during workouts (est.).

Global Wellness Institute · Feed.FM Wellness & Workout Music Report · management estimates from disclosed platform MAU and streaming data.

The Problem

Users are doing work
the music should do.

A workout has phases. Music doesn't know any of them. So users compensate — manually, mid-set, every session.

They curate
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Hours of pre-work.

73% of workout listeners build dedicated playlists — sequencing by BPM, energy, and session type. Craft work the system should do.

They skip
1 in 4

Flow, broken.

One in four songs is skipped within 30 seconds during workouts. Wrong tempo. Wrong energy. Every skip breaks form, breaks heart-rate zone, breaks flow.

They quit
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Sessions abandoned.

40% of users abandon a workout after three or more interruptions. The session ends not because the body gave up — but because the music kept fighting it.

The existence of "best workout playlist" as a category is evidence the default product is broken. Users are paying — in time, attention, and abandoned sessions — for a problem the system should solve.

Why Now

The simple fix failed.
The hard one is now possible.

What's been tried — tempo matching is dead

2015Spotify RunningDiscontinued 2018
2017Nike+ Run Club tempoQuietly removed
2017Weav Music + 3 majorsDeadpooled 2022
2019Apple Music workout tempoNever shipped

The lesson: tempo alone isn't enough. Adaptation needs structure, biometrics, and real-time response.

What's changed — biometric data has no home

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wearables generating biometric streams. Apple Watch, Garmin, Whoop, Polar, Oura — infrastructure that didn't exist in 2018.

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drop in AI inference cost since 2020 — resolving the key scale-up bottleneck.

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currently flowing from biometrics into music. Every wearable knows what your body is doing. The music app on the same wrist doesn't.

The window is open: the simple version is disproven, the infrastructure is in place, and no one has shipped the hard version yet.

Technology

Three pillars.
One adaptive system.

01 — AI MUSIC INDEXER

Every track, deeply understood.

Server-side AI analyses your entire music catalogue, deconstructing each track — structure, energy profile, sonic character — and building a proprietary metadata file that is the foundation of adaptive audio.

Server-side AICatalogue processingScalable indexing
02 — METADATA LAYER

A digital map of every song.

Each metadata file captures song structure, EQ profiles, and dynamic range — a rich digital map giving the audio engine the granular understanding it needs to personalise sound in real time.

Song structureEQ profilingDynamic range
03 — AUDIO ENGINE

Music individualised. Delivered anywhere.

Metadata fuses with live user data — biometrics, motion, context — inside AURNO's player engine, delivering personalised audio via a white-labelled SDK across any device or platform.

Real-time personalisationWhite-label SDKAny device
How It Works

From catalogue to personalised sound.

STEP 01

Index

AURNO's AI indexer ingests your catalogue server-side, generating a proprietary metadata file unique to each song.

STEP 02

Map

Each file becomes a deep digital map — structure, EQ, and energy profile in a format the engine can act on.

STEP 03

Fuse

Metadata streams to the player engine in real time, where it combines with live biometrics, motion, and context.

STEP 04

Deliver

Individualised audio, output through a white-labelled SDK — embedded invisibly into the platforms your users already use.

Inside The Stack

Where AURNO sits in your stack.

Three streams converge on the device: AURNO's metadata, the music your platform already licenses, and live wearable data — fused in real time by the AURNO Player Engine.

Hover or tap any node
INPUT STREAMS TO THE USER PARTNER ECOSYSTEM Partner fitness app UX · workouts · training plans · social 01 · AURNO CLOUD Metadata stream Structure · EQ · energy · dynamics 02 · MUSIC SERVICE Music stream Apple Music · Spotify · Partner 03 · WEARABLES Live body data GPS · Motion · Heart rate AURNO PLAYER ENGINE Real-time fusion Metadata + music + biometrics White-label SDK · runs on device Watch Phone Earbuds Equipment Embedded natively in partner hardware OUTPUT Adaptive audio One continuous, personal mix

Partner Integration

Built for platforms at scale.

AURNO is a B2B infrastructure layer — we process, partners license. Designed to integrate directly into fitness platforms, equipment, and health applications, on top of the music rights you already hold.

AURNO API

A clean, documented API for integrating adaptive audio intelligence into any fitness platform, app, or connected hardware. Low-latency, high-reliability, built for production at scale.

Platform SDK

Native SDKs for iOS, Android, and embedded systems enable deep integration with existing wearable and equipment ecosystems — without re-engineering your stack.

Engagement Data

AURNO's adaptive layer directly addresses the 50%+ dropout rate in fitness programs. Partners receive engagement analytics tied to audio adaptation events.

Custom Tuning

Enterprise partners can configure AURNO's models to their use case — from high-intensity training to rehabilitation, recovery, and focus-oriented wellness.

What We Believe

Four principles.

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Sound should be personalized, not prescribed.

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Technology should amplify human potential, not distract from it.

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Intelligence is most powerful when it feels invisible.

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The best experiences happen in real time.

Our Journey

How we got here.

2022

Initial Patents Awarded

Core intellectual property established around real-time adaptive audio systems and biometric-driven signal processing.

2024

R&D Phase & Early Partnerships

Development of the AURNO inference engine, with early validation partnerships across fitness hardware and platform integrations.

2026

AURNO Founded

AURNO launches as a B2B adaptive audio intelligence company. The platform enters its first commercial partner integrations.

Get In Touch

Ready to bring adaptive audio to your platform?

We work with fitness platforms, equipment manufacturers, and wellness applications. If you're building something performance-oriented, we want to hear from you.

hello@aurno.io