What is a Knowledge Graph?

A Knowledge Graph is a structured representation of entities and the relationships between them, stored in a graph database and queried with traversal or graph-query languages. In commerce it captures products, categories, attributes, customers and content as nodes with typed edges, giving both humans and LLM agents a deterministic source of truth alongside Vector Search.

Definition

Each node carries a stable identifier and a set of properties, while edges encode semantically meaningful relationships such as "belongs to category", "is a variant of" or "is compatible with". Schemas can follow standards like Schema.org for SEO surfaces or domain-specific ontologies for richer modelling. Population mixes ETL from PIM and ERP feeds with model-driven extraction from unstructured sources such as reviews or supplier PDFs. Queries traverse multiple hops to answer questions like "which laptops compatible with this dock are in stock in Berlin", which classical relational schemas struggle with. In AI stacks Knowledge Graphs combine with Embeddings: semantic similarity finds candidate nodes, graph traversal validates the structural relationship.

Why it matters

LLMs are bad at relational reasoning over many entities, and Hallucination spikes when they have to chain facts from prose. A Knowledge Graph turns those chains into verifiable lookups, which is critical for grounded answers in Conversational Commerce and AI Merchandising. It also stabilises Personalization: the same canonical entities feed search, recommendations and content, so a customer's preference for a brand or material is consistent across surfaces. In a Composable Commerce architecture the graph runs as a service queried from the Storefront API, the Recommendation Engine and agent tools.

Use cases

A product graph powers compatibility filters for tech accessories and feeds an LLM Tool Use endpoint so a chat agent answers fitment questions deterministically. A content graph links articles to products and customer segments, which lets an Agentic SEO workflow find orphan content and propose internal links. A customer graph encodes households and roles so a B2B copilot can resolve who is allowed to place which orders.

Related

Explore Performance and Core Web Vitals · Composable Headless Frontend.