# EVERA Music Experience: AI-Readable Project Brief

Canonical project page: https://markvizion.com/projects/evera-music-experience
Live application: https://evera-music-landing.netlify.app/
Owner: Mark Barnes / MarkVizion
Category: music
Stack: ACE-Step, Python, SQLite, React, Web Audio API

## Summary

An autonomous music creation engine that generates professional-quality tracks across 20+ genres. 7 curated radio stations, 9.9/10 quality rating.

## Problem

Generative music is easy to create once, but hard to package as a repeatable listening system with quality control and discovery.

## Architecture

- AI music generation pipeline produces tracks across genre categories.
- Quality scoring, metadata, and station logic turn raw outputs into an entertainment surface.
- React and Web Audio provide the listener-facing experience.

## Evidence

- Live hosted application: https://evera-music-landing.netlify.app/
- Live hosted music experience with curated stations.
- 20+ genre range and quality scoring signal a repeatable generation pipeline.
- Shows AI output curation, media product design, and entertainment packaging.

## Tradeoffs

- The product value comes from curation and experience design, not raw generation alone.
- Quality scoring must be tuned around listener expectations, not model novelty.

## Outcome

A deployed AI music system that demonstrates generative media operations and productization.

## Authority Signal

Evidence for AI-native entertainment systems and creative infrastructure.

## Keywords

AI Music, Generative Audio, 20+ Genres, 9.9/10 Quality, ACE-Step, Python, SQLite, React, Web Audio API, Evidence for AI-native entertainment systems and creative infrastructure.