Content Taxonomy & Tagging

content-that-organizes-itself

Content That Organizes Itself Taxonomy & Tagging uses trained ML models to automatically classify and tag content as it is created. New articles are instantly categorized by topic, audience, intent, and sentiment — without manual tagging by authors. Hierarchical taxonomies support unlimited depth with faceted navigation. Cross-content relationships are inferred from semantic similarity, enabling automated 'related content' recommendations.

Taxonomy Specifications

Hierarchy

Unlimited depth with parent-child relationships

Auto-Tagging

ML-based topic, audience, intent, sentiment classification

Facets

Multi-dimensional filtering with AND/OR logic

Relationships

Semantic similarity-based content linking

Bulk Operations

Mass re-tag, merge taxonomies, import/export

features

faceted: true

ai auto tag: true

hierarchical: true

relationships: true

Relationships