Agentic Crowd Intelligence for DJs

One mix. Several audiences. Several reactions.

AI Clubber Agents model different tastes, energy needs, attention patterns and nightlife behaviors.

Agent anatomy

Each agent profile carries a taste profile, an energy need, a patience level, a novelty response and an attention pattern.

Core archetypes

Festival Energy Seekers, Underground Heads, Social Party Crowd, Core Fans, Curious Newcomers, DJs & Producers and other listener profiles.

Context effects

Venue, crowd size and set time reweight the population, so the same mix meets a different room.

Segment-level response

Your room is modeled as four to six weighted audience segments, not as thousands of individually simulated people. Each segment reacts to the set, and the segments are aggregated into engagement, retention, peaks and attention risks.

Limits and confidence

Agent profiles are behavioral models, not people. Predictions are confidence-weighted and remain directional.

Illustrative simulation interface. Results vary by mix and crowd context.

How crowd simulation works How it works

AGENTIC CROWD INTELLIGENCE FOR DJs

Inside the SOONOS Multi-Agent Crowd Engine.

Upload your mix. Our engine measures the audio, models the room, and shows you how the crowd could react — before the show.

Upload

Drop your set. We accept WAV, MP3, FLAC and direct imports.

Measure

DSP reads energy, structure, transitions and DJ signature.

Simulate

AI Clubber Agents react inside the modeled room and crowd.

Live crowd preview

Simulated agent reaction across a short set arc

45%

engagement

Agents reacting in real timePause on hover

THE IDEA

Don’t just analyze the mix. Simulate the room.

A set does not exist in isolation. The venue, time, crowd and musical expectations change how it lands. SOONOS models that context with AI Clubber Agents — then lets them experience your mix.

Build the crowd

Choose the room, set time and crowd size.

Add the mix

Upload a file or import your set.

Run the simulation

Watch different agent profiles react across the timeline.

Prepare the show

See what could win the room, lose attention or need a different move.

See How It Works

BUILD YOUR ROOM

Every crowd is different. Build yours.

Give SOONOS three signals. The Multi-Agent Crowd Engine builds the rest.

Where are you playing?

ClubFestivalBeach ClubPrivate PartyRadio / Online

How many people?

1005001,0005,00010,000

When is your set?

OpeningSunsetPeak TimeAfter-hoursClosing

Your virtual crowd is ready.

2,800 Energy Seekers
2,100 Underground Explorers
1,600 Social Clubbers
1,200 Core Fans
900 Curious Newcomers
700 DJs & Producers
700 Other Listener Profiles

Illustrative simulation interface. Results vary by mix and crowd context.

MEET THE AGENTS

Not one audience. Thousands of perspectives.

Every AI Clubber Agent has its own music taste, energy needs, attention pattern and sensitivity to the way a set develops.

Maya

Underground Explorer

Looks for depth, progression and selections she has not heard before.

High patience · High novelty sensitivity

Leo

Energy Seeker

Responds to momentum, payoff moments and a room that keeps moving.

High energy need · Lower build tolerance

Nina

Social Clubber

Follows collective energy and reacts when the room reacts.

High social influence · Broad taste

Kai

DJ & Producer

Notices transitions, structure, restraint and technical decisions.

High technical sensitivity · High attention

Sam

Curious Newcomer

Open to discovery, but needs enough clarity and momentum to stay engaged.

High curiosity · Medium retention

Their individual responses become your crowd intelligence.

Explore AI Clubbers

LET THEM LISTEN

Your mix enters the room.

SOONOS synchronizes the mix timeline with every audience profile. Energy, progression, transitions, novelty and context shape how each segment may respond.

Watch Demo Simulation

· 8,472 agents engaged
· Underground profiles rising
· Casual attention declining
· Crowd momentum recovering
· Peak reaction detected at 42:16

Illustrative simulation interface. Results vary by mix and crowd context.

CROWD INTELLIGENCE

See what happened inside the room.

Move beyond a single score. Understand how different listeners experienced each chapter of the set — and what to change before the show.

84%

Predicted Crowd Engagement

78%

Predicted Retention

42:16

Crowd Peak

31:20

Attention Risk

Who you wonWho you lostMoments that changed the roomWhat to change before the show

Explore a Crowd Report

Illustrative simulation interface. Results vary by mix and crowd context.

EVIDENCE, NOT VIBES

The model is built on measured mixes, not opinions.

Before predicting a room, SOONOS measures sets. Every number below comes from our own database and every decoded mix is public — open one and check the timestamps yourself.

2,000+

Mixes analyzed end to end

Full audio measurement, not metadata

4,900+

Reference mixes catalogued

Used to anchor the artistic scale

349

Reference DJs decoded

Signature profiles across genres

100%

Claims tied to timestamps

No unevidenced penalties or praise

Browse decoded mixes Read the methodology See a full mix report

Figures reflect the SOONOS measurement database and are updated as the corpus grows.

SEE IT BEFORE YOU SIGN UP

Get a sample Crowd Intelligence Report.

We send you one complete report — the metrics, the key moments and the recommended moves — so you can judge the output before creating an account.

One email. No spam, unsubscribe anytime.

CONTEXT CHANGES EVERYTHING

One mix. Different crowds. Different outcomes.

A sunset beach set, an underground after-hours room and a festival mainstage do not listen the same way.

Ibiza Beach Club · Sunset

88%

Strong emotional and social response

Berlin Club · After-hours

71%

Strong depth, weaker commercial moments

Festival · Peak Time

79%

Good peaks, attention risk during long builds

Illustrative simulation interface. Results vary by mix and crowd context.

Compare Crowd Scenarios

UNDER THE ROOM

Inside the SOONOS Multi-Agent Crowd Engine.

SOONOS combines agent-based audience modeling with timeline-level music intelligence. Each agent profile interprets the same set through a different behavioral lens.

Audience Generation

Creates weighted listener populations from venue, size, set time and audience context.

Agent Behavior

Models taste, patience, energy sensitivity, novelty response and attention patterns.

Mix Intelligence

Maps energy, structure, transitions and musical events across the full timeline.

Crowd Response

Aggregates agent-level reactions into engagement, retention, peaks and attention risks.

Multi-agent audience generationBehavioral preference modelingContext-aware simulationTimeline-level reactionsConfidence-weighted predictionsDSP-supported mix signals

Discover the Engine

THE MEASUREMENT LAYER

A simulation is only as credible as what it measures.

Advanced Mix Intelligence measures the audio itself — energy, structure, transitions, storytelling, selection and technical consistency — with timestamped evidence. The agents never react to a guess; they react to measured signals. That measurement layer is what separates SOONOS from an opinion generator.

Energy and narrative timeline
Transition intelligence
Technical consistency
Track-selection behavior
DJ signature
Timestamped recommendations

Explore Mix Intelligence View Full Mix Report

WHY WE BUILT THIS

A set is not a file. It is a room.

Scoring a mix in a vacuum tells a DJ what a machine thinks of their technique. It never tells them what the floor at 2am in a 500-capacity basement would have done with it. We think the useful question was always the second one — so we built the room instead of the grade.

Read the SOONOS philosophy

BUILT FOR THE ROOM

From the bedroom to the mainstage.

For DJs

Test a set against the crowd you expect before the booking.

For Promoters

Understand how a submitted mix may fit a specific room and audience.

For DJ Schools

Turn abstract feedback into audience-context learning.

For Competitions

Add crowd-context intelligence to mix screening and jury review.

Simulation, not certainty.

Music remains human, contextual and unpredictable. SOONOS provides directional crowd intelligence based on musical and audience signals. It does not guarantee how a real audience will behave.

How we know what we know

Measured

The audio itself: energy, tempo stability, loudness, transitions and structure, extracted by signal processing with timestamps you can check.

Modeled

The audience response: how weighted listener segments may react to those measured signals in a given room, size and set time.

Never claimed

That a real crowd will behave exactly like the model. Predictions are directional and confidence-weighted.

How SOONOS Builds Confidence

YOUR NEXT ROOM STARTS HERE

Build the crowd before you face it.

Create your AI audience, add your mix and discover how the room could move.

Watch a Simulation

No crowd configuration expertise required.

One mix. Several audiences. Several reactions.

Agent anatomy

Core archetypes

Context effects

Segment-level response

Limits and confidence

Inside the SOONOS Multi-Agent Crowd Engine.

Upload

Measure

Simulate

Don’t just analyze the mix. Simulate the room.

Build the crowd

Add the mix

Run the simulation

Prepare the show

Every crowd is different. Build yours.

Not one audience. Thousands of perspectives.

Maya

Leo

Nina

Kai

Sam

Your mix enters the room.

See what happened inside the room.

The model is built on measured mixes, not opinions.

Get a sample Crowd Intelligence Report.

One mix. Different crowds. Different outcomes.

Inside the SOONOS Multi-Agent Crowd Engine.

Audience Generation

Agent Behavior

Mix Intelligence

Crowd Response

A simulation is only as credible as what it measures.

A set is not a file. It is a room.

From the bedroom to the mainstage.

For DJs

For Promoters

For DJ Schools

For Competitions

Simulation, not certainty.

How we know what we know

Build the crowd before you face it.

Drop your mix. Explore your session.