Case study · Music rights management
Composer Sync.
An AI-powered asset analysis platform that enables users to upload audio files, automatically analyze them using AI, and generate professional reports for legal, audit, and rights-management purposes.
- What we built
- Web app with AI analysis and report generation
- Stack
- Next.js, TypeScript, Node.js, API Services
- Services
- Web appAI analysis pipelinePDF report generation
About the project
What is Composer Sync?
This project involved building an AI-powered asset analysis platform that enables users to upload audio files, automatically analyze them using AI, and generate professional reports for legal, audit, and rights-management purposes. The platform was designed as a secure, web-based application with user authentication, cloud storage, AI processing, structured results visualization, and automated PDF report generation. The solution streamlined a traditionally manual process by transforming uploaded media into structured insights within minutes.
The problem
What was slowing them down.
- 01
Asset owners rely on manual workflows
Asset owners and rights holders often rely on manual workflows to analyze audio assets, organize metadata, maintain rights information, and prepare supporting documentation.
- 02
Manual collection and organization
Manual collection and organization of rights-related information.
- 03
Time-consuming analysis
Time-consuming analysis and reporting processes.
- 04
Lack of centralized storage
Lack of centralized storage for user identity and ownership data.
- 05
Difficulty generating consistent documentation
Difficulty generating consistent documentation for legal and audit purposes.
- 06
Need for secure handling
Need for secure handling of uploaded files and sensitive information.
- 07
Need for a centralized platform
The client required a centralized platform capable of securely processing uploaded assets and generating structured AI-powered insights and reports.
The solution
What we built.
A cloud-based platform
We developed a cloud-based platform that combines secure authentication, asset ingestion, AI analysis, and automated report generation into a single workflow.
- Secure user authentication and profile management.
- Identity Vault for storing rights and ownership information.
- Audio file upload with validation and resumable uploads.
- AI-powered analysis pipeline for extracting structured metadata.
- Results dashboard with downloadable CSV exports.
- Automated PDF report generation using user profile and analysis data.
- Background processing architecture for handling long-running AI tasks.
- Secure cloud storage with automated file lifecycle management.
- The system was built with future scalability in mind, allowing expansion into multi-tenant environments without major architectural changes.
Results
What changed.
Results & impact
Reduced manual analysis
Reduced manual analysis and documentation effort.
Faster turnaround
Faster turnaround from upload to report generation.
Improved consistency
Improved consistency across generated reports.
Centralized management
Centralized management of rights and ownership information.
Enhanced security
Enhanced security through authentication and controlled access.
Scalable foundation
Scalable foundation for future AI-driven asset management features.
A streamlined workflow
The result was a streamlined workflow that transformed complex asset analysis into a simple upload-and-generate experience.
Key challenges
The hard parts, and how we solved them.
Handling large file uploads
Implemented resumable uploads to ensure reliability during unstable network conditions.
Data security & privacy
Applied secure authentication, encrypted communication, and controlled access to sensitive user information.
Long AI processing times
Built an asynchronous job processing system with status polling and retry mechanisms.
Future scalability
Designed the database and architecture to support future multi-tenant expansion without requiring major system redesigns.
Report accuracy
Combined structured user profile data with AI-generated insights to ensure consistent and reliable report outputs.
Tech stack
What it runs on.
- Frontend & backend
- Next.jsTypeScript
- Backend
- Node.jsAPI Services
- Database & authentication
- SupabaseRow-Level Security (RLS)
- Storage
- Cloudflare R2
- AI layer
- AI Adapter ArchitectureRAG-Ready Processing Pipeline
- Infrastructure
- Async Job QueueServer-Side PDF RenderingSecure HTTPS Deployment
Process
How we got there.
01User authentication
User registers and verifies their account. · Secure login establishes an authenticated session.
02Identity Vault setup
User completes ownership and rights information. · Data is securely stored for future report generation.
03Asset upload
User uploads supported audio files. · Validation checks file type and size. · Files are securely stored in cloud storage.
04AI processing
Analysis jobs are processed asynchronously. · Users receive real-time status updates.
05Results review
AI-generated metadata and insights are displayed. · Users can review and export structured results.
06Report generation
Identity Vault information and AI analysis results are combined. · A professional PDF report is generated and downloaded.
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