OUR PROCESS

Quick Overview

Vibeset's proprietary engine transforms your musical input into perfectly curated setlists through a sophisticated 3-phase process that combines machine learning, professional DJ principles, and creative intelligence.

Process Summary

USER INPUTSML PROCESSINGPROFESSIONAL SETLIST

The simplified diagram below shows this 3-phase transformation at a glance.

Audio Waveform

User Inputs

  • Artist preferences
  • Specific song selections
  • Genre preferences
  • Mood & energy levels
  • Vibe characteristics
  • Duration requirements

Final Output

  • Optimized track sequence
  • Creative setlist title
  • Journey description
  • DJ transition insights
  • Precise timing analysis
  • Artist distribution metrics
1

Song Pool Building

Intelligent candidate selection using semantic embeddings

NLP Embedding

Natural language processing converts preferences into vector embeddings

Similarity Search

Database queries find ~500 matching candidates using cosine similarity

Artist Classification

Categorizes tracks by requested vs. similar artists for balance

2

DJ-Principle Curation

Professional selection algorithms ensure optimal track variety

Duration Planning

Calculates optimal track count and timing flexibility

Artist Balance

Prevents dominance while maintaining representation

Smart Scoring

Multi-factor analysis for track prioritization

Duplicate Detection

Fuzzy matching eliminates similar versions

3

Intelligent Sequencing

LLM's create a perfect flow for creative storytelling with music

Track Scrambling

Randomizes input order for unbiased AI analysis

DJ Sequencing

Professional energy arc management and transitions

Creative Generation

Compelling titles and narrative descriptions

Transition Insights

BPM matching and mixing recommendations