For promoters and venues
Understand how a submitted mix may fit a specific room, crowd size and slot.
Agentic Crowd Intelligence for DJs
Evaluate the fit between a mix and a room.
Promoters, venues, schools and competitions can review submissions in the audience context that actually matters.
Run a PilotFor DJ schools
Turn abstract feedback into audience-context learning students can act on.
For competitions
Add crowd-context intelligence to mix screening and jury review.
Illustrative simulation interface. Results vary by mix and crowd context.
[ 01 ] How a pilot runs
One room. Every submission judged in the same context.
Describe the room
Venue type, capacity, slot and expected audience. The Multi-Agent Crowd Engine builds a weighted audience for that exact context.
Collect the submissions
Applicants send a link or a file. Each mix goes through Advanced Mix Intelligence: energy, structure, transitions, selection and storytelling.
Review in context
Every submission is simulated against the same room, so you compare fit for your night — not raw taste or follower count.
[ 02 ] What your team receives
A comparable read on every applicant.
Predicted engagement
How the modelled room responds across the set, minute by minute.
Predicted crowd retention
Where the room stays, where attention drifts, where it comes back.
Shortlist ranking
Submissions ordered by fit for your specific slot, with the signals behind each position.
Consistent criteria
The same audience context for every applicant, so screening stays comparable and defensible.
[ 03 ] Who uses it
Built for the people who choose the line-up.
Promoters and venues
Screening residents, warm-up slots and guest bookings. See whether a mix carries an opening slot or a peak-time room before you commit a date.
- Slot-by-slot fit
- Opening vs peak-time reading
- Saved rooms for recurring nights
DJ schools
Turn abstract feedback into audience-context learning. Students see which moments moved the room and which weakened it, with timestamps.
- Timestamped evidence
- Progress across submissions
- Shared vocabulary for tutors
Competitions and calls
Add crowd-context intelligence to jury review. Pre-screen large volumes, then give the jury a consistent brief per finalist.
- High-volume pre-screening
- Jury-ready summaries
- Transparent, repeatable criteria
Labels and radio
Assess guest mixes and demo sets against the audience you actually broadcast to, not a generic listener.
- Audience-profile match
- Attention-risk moments
- Comparable reads across artists
[ 04 ] Questions
Does this replace a human jury?
No. Crowd simulation is directional intelligence used to pre-screen and to structure discussion. The decision stays with your team.
What do applicants need to send?
A mix link or an audio file. SOONOS handles SoundCloud and Mixcloud links as well as direct uploads.
Can we use our own room settings?
Yes. A room is saved once — venue, capacity, slot, audience mix — then reused for every submission in the same call.
How accurate is it?
Predictions are confidence-weighted models of audience behaviour, not guarantees. They are built to compare submissions under identical conditions.
Run a pilot on your next call for DJs.
Send us one room and a batch of submissions. We set up the audience context and return a comparable read on every applicant.