Taxonomy & Classification Management System
Governed taxonomy and ML-assisted classification system to manage categories and attributes across enterprise catalogs.
Problem: Catalog teams needed a consistent taxonomy workflow with a reliable search interface and frontend architecture for complex category rules.
Outcome: Built an Angular-led taxonomy application with AI-assisted review queues and faster classification accuracy at enterprise scale.
Problem
Enterprise catalogs need consistent taxonomy and classification to keep search, analytics, and downstream systems aligned.
Solution / Approach
Built a governance platform with hierarchical taxonomy control, review queues, and ML-assisted suggestions embedded directly in editorial dashboards.
Architecture
- Central taxonomy services with versioned category rules.
- ML-assisted classification predictions surfaced in UI.
- Review queues for editors with audit logs and rollback.
Key Features
- Hierarchical taxonomy governance with approval workflows.
- ML suggestions with confidence-based review prioritization.
- Validation rules to prevent invalid category assignments.
What I Learned
Combining human governance with ML suggestions works best when confidence, review load, and auditability are explicit.