Question 1

What is a knowledge graph?

Accepted Answer

A knowledge graph is a structured representation of entities (people, products, places, concepts) and the relationships between them. It's the layer AI answer engines and autonomous agents read from when they retrieve, reason over, and cite your brand.

Question 2

How is a knowledge graph different from schema markup?

Accepted Answer

Schema markup is one serialization format for expressing entities and relationships. A knowledge graph is the underlying model — it can be expressed in schema.org, JSON-LD, RDF, or a graph database, and it stays coherent as your content grows.

Question 3

Do I need a graph database?

Accepted Answer

Not necessarily. Many knowledge graphs are stored as JSON-LD in your CMS, as rows in a relational database, or as triples in a dedicated store. The architecture matters more than the storage engine.

Question 4

How long does a knowledge graph build take?

Accepted Answer

Foundational entity models and structured data typically ship in 4–6 weeks. Full knowledge graph builds with validation, ingestion, and ongoing curation run 8–16 weeks depending on scope.

Question 5

Will a knowledge graph improve AI search visibility?

Accepted Answer

Yes — a well-built graph is the layer that makes your brand legible to answer engines. It increases citation rates, reduces entity ambiguity, and gives agents the structured facts they need to trust your content.