Content graph
Description
A content graph turns disconnected content repositories into connected ecosystems. It links content items using metadata, taxonomy and semantic relationships so that each piece can "understand" its context within the wider collection.
Unlike a knowledge graph, which maps real-world entities (people, places, concepts), a content graph focuses on the content itself – how assets connect, complement and evolve. By representing those connections visually and structurally, it allows systems to find, recommend and reuse information more intelligently.
Structured content plays a key role. When every component follows consistent rules for format, tagging and metadata, content can be automatically linked, queried and recombined. This makes it possible to deliver context-aware recommendations, improve semantic search and power AI-driven insights. For enterprises managing thousands of assets across channels and languages, a content graph provides the foundation for content intelligence – turning stored information into actionable knowledge.
Example use cases
- Content discovery: Helping users find related or supporting materials instantly.
- Semantic search: Understanding meaning and intent, not just keywords.
- Personalization: Recommending content based on user behavior and context.
- Knowledge discovery: Revealing hidden patterns and connections across repositories.
- Governance: Maintaining consistency in metadata, tagging and relationships.
Key benefits
RWS perspective
At RWS, content graphs are central to building intelligent, connected content ecosystems. Through Tridion, our enterprise content management platform, we help organizations model relationships between assets so content becomes easier to find, manage and deliver – at scale.
By combining structured content design, Semantic AI and our deep localization expertise, we enable clients to link content meaningfully across languages and markets. The result is a dynamic, searchable web of knowledge that evolves as your business grows. Our approach blends human understanding with intelligent automation, turning static repositories into living ecosystems of information – where every piece of content contributes to a bigger picture.