Build the knowledge graph that makes AI trust your brand

An entity is a uniquely identifiable concept — a person, organisation, product, location, or idea. In SEO, entities are the structured knowledge representations that search engines and AI systems use to understand and categorise information. Your brand, team members, and products are all entities.

A knowledge graph is a structured database of entities and their relationships. Google's Knowledge Graph, for example, contains billions of entities and understands how they relate to each other. When AI systems need to verify who a brand is or what it does, they consult knowledge graphs.

AI systems need to recognise your brand as a distinct entity before they can recommend it. Entity SEO builds the structured knowledge signals — schema markup, knowledge graph presence, entity relationships — that AI systems use to identify and trust your brand.

Yes. Traditional SEO focuses on page-level optimisation (keywords, backlinks). Entity SEO focuses on brand-level recognition. You can rank well for specific keywords but still be invisible to AI systems if your entity signals are weak.

Schema.org is the structured data vocabulary used to define entities in machine-readable format. It tells AI systems your organisation type, team members, products, reviews, and expertise. Without Schema.org markup, AI systems have to guess what your brand is — and they often guess wrong.

Knowledge Graph inclusion requires consistent entity signals: structured data on your site, Wikidata entries, consistent NAP (Name, Address, Phone) data, authoritative mentions across the web, and Wikipedia references for larger entities. We build these signals systematically.

Entity disambiguation is ensuring AI systems don't confuse your brand with similarly-named entities. If there's another company with your name, disambiguation signals (unique identifiers, @id, sameAs links) help AI systems distinguish between you.

Schema markup changes take effect within weeks as crawlers re-index. Knowledge graph and entity authority improvements typically show measurable results in 2-4 months. Full entity authority compounds over 6-12 months.

Topical authority is AI systems' confidence that your brand is an expert on a specific topic. It's built through deep, structured content clusters, consistent expertise signals, and entity relationships that demonstrate domain knowledge.

Absolutely. Google increasingly uses entity understanding for rankings. Brands with strong entity signals rank better for brand queries, get Knowledge Panels, and appear in related searches. Entity SEO helps both traditional and AI search.

Structured data (Schema.org) is how you define entities in a machine-readable format. It's the implementation layer of entity SEO — the code that tells AI systems 'this is our organisation, these are our products, these are our team members.'

We track knowledge graph presence, schema completeness scores, AI citation frequency, entity recognition across platforms, and competitor entity strength. Together these metrics give a comprehensive view of your entity health.

Very. Small businesses often lack any entity presence — they're invisible to AI systems. Establishing even basic entity signals (proper schema, Google Business Profile, consistent NAP data) can dramatically improve AI visibility.

Schema markup is one tool within entity SEO. Entity SEO is the broader strategy of building your brand's identity in knowledge systems. Schema markup defines your entities in code; entity SEO also includes knowledge graph development, topical authority, and cross-platform entity signals.

Pricing depends on your current entity state, industry complexity, and the number of entities to develop. A single-location business with basic entity needs costs less than a multi-location enterprise. Contact us for a scoped quote.