AI Music Ops | Graph-Powered Operations Platform

A private group managing music operations needed a platform that could model complex relationships between artists, tracks, royalties, and distribution channels, and use AI to optimize daily workflows.

An AI-powered operations platform using a graph database (Neo4j) to model the interconnected relationships in music business data. Combined with React and PostgreSQL for the application layer. Key capabilities:

Graph-based data modeling: Neo4j maps artist-label-distributor-track relationships, enabling queries that relational databases struggle with

AI-powered recommendations: Automated suggestions for playlist placement, collaboration opportunities, and revenue optimization

Operational dashboards: Daily task management, pipeline tracking, and team coordination

Dual database architecture: Neo4j for relationship queries, PostgreSQL for transactional data

Neo4j (graph database), PostgreSQL (transactional data), React (frontend), AI/ML integration

Successfully deployed and actively used by the private group in their daily operations. The graph database approach surfaced relationship insights that were invisible in their previous spreadsheet-based workflow.