If you want AI search to cite your business, stop optimising pages and start defining an entity. AI systems built on GraphRAG don't just match keywords to text anymore — they build a graph of things (people, companies, products, places) and the relationships between them, then pull answers from that graph. To get quoted, you need to be a node the model recognises, trusts, and can connect to a topic.
Here's the shift in one sentence: old search retrieved documents, new AI search retrieves entities and the facts attached to them. A page that ranks fine on Google can be invisible to an AI answer if the model can't work out who you are, what you do, and why you're a reliable source on the question.
The good news for smaller operators: most of your competitors have no plan for this. A coherent, consistent entity is a slow, boring job that big brands often fumble across dozens of pages — and it's something a focused small business can actually get right.
What entity-first retrieval actually means
Entity-first retrieval means the AI answers a question by looking up structured facts about known entities, not by scanning a pile of loosely matched pages. GraphRAG (graph-based retrieval-augmented generation) is the technique behind it: the model organises what it knows into a knowledge graph — nodes for entities, edges for how they relate — and reasons over that graph before writing an answer.
Plain example. Ask an AI "who offers GDPR-friendly hosting in the EU for freelancers?" A keyword system hunts for pages containing those words. A GraphRAG system looks for entities tagged as hosting providers, filters by attributes like EU-based and serves freelancers, checks which ones are corroborated across multiple sources, and cites those. If your business isn't a clean node with those attributes attached, you don't enter the shortlist — no matter how good your copy is.
This is why two things now matter more than they used to: clarity (can a machine state plainly what you are?) and corroboration (do independent sources agree on the same facts about you?). Contradictions break the graph. If your address differs across three directories, the model either picks one, hedges, or drops you.
Fix your identity facts first: NAP and the obvious stuff
Before anything clever, make your core identity facts identical everywhere they appear online. Name, address, phone (NAP) plus your business category, founding details and key people. This is the least glamorous work in SEO and it's now the most valuable move you can make for AI citation.
Inconsistency is the silent killer. "Acme Ltd" on your site, "Acme Limited" in your Google Business Profile, and "ACME" on LinkedIn read as three fuzzy references to a machine — not one confident entity. Pick one canonical form of every fact and enforce it.
Work through this checklist:
- Exact legal name — one spelling, one capitalisation, used everywhere including footer, About page and directory listings.
- Single canonical phone and address — same format down to the punctuation.
- Consistent category — describe what you do in the same words across your site, Google Business Profile and social bios.
- Same founding year and founder names — small mismatches erode trust signals.
- One primary domain — redirect the rest to it so link and mention equity consolidates on a single node.
Spend an afternoon auditing your top 15 mentions of the business across the web. You'll almost certainly find a contradiction. Fix it.
Write an About page a machine can parse
Write your About page as a plain statement of facts about the entity, not a founder's story. Both matter, but lead with the machine-readable spine: who you are, what you do, who you serve, where you operate, when you started, and what makes your claims verifiable.
The About page is where AI models expect to find your entity definition, so give them unambiguous sentences. "TPC Hosting is an EU-based web hosting company serving freelancers, solopreneurs and small businesses" is a sentence a graph can absorb. "We're passionate about empowering your digital journey" is noise — it names no attribute a model can attach to your node. Put the concrete claims in short declarative sentences near the top, then add the personality below.
State your relationships explicitly too, because edges are what GraphRAG connects. Name your service categories, the regions you cover, the tools or standards you work with (GDPR, specific CMS platforms), and any partnerships. Each named relationship is a potential edge that links your entity to a topic someone will ask about.
Structured data is how you speak the graph's language
Structured data (schema.org markup) is the most direct way to hand an AI the facts you want attached to your entity. Instead of hoping a model infers your details from prose, you state them in a format built for machines.
At minimum, mark up your organisation and connect your identity to your official profiles. Drop a JSON-LD block like this into the of your homepage and adapt every value to your own facts:
| Property | What to set it to |
|---|---|
| @type | Organization (or LocalBusiness if you serve a physical area) |
| name | Your one canonical legal name |
| url | Your single primary domain |
| sameAs | Array of your LinkedIn, Wikidata, Crunchbase and social URLs |
| description | One-sentence plain description matching your About page |
| foundingDate / founder | Consistent with everywhere else |
| areaServed | The regions you actually cover |
Here's a copy-paste starting point:
The sameAs property is the quiet hero. It tells the graph "these separate profiles are all the same entity as me," which merges scattered mentions into one strong node. To get a free Wikidata entry, sign in at wikidata.org, click Create a new item, add a label, description and a few sourced statements (official website, inception, country), then paste the resulting Q-number URL into your sameAs array. For your Google Business Profile category, open your profile, click Edit profile → Business category, and copy that exact wording into your schema description and About page so the three agree word-for-word.
Add Article and Person (for author) markup to your posts, and FAQPage where it fits naturally. Before you ship, run the live URL through Google's Rich Results Test: paste the URL at search.google.com/test/rich-results, hit Test URL, and clear every error and warning under the Organization result. Then run the same page through validator.schema.org to catch anything Google ignores. Broken markup is worse than none.
Turn internal links into GraphRAG edges
Publish clusters of related content around a few subjects you genuinely know, but treat every internal link as a deliberate edge in the graph, not just navigation. When page A links to page B with descriptive anchor text, you're asserting a relationship the model can read: this entity — this topic — this sub-topic. Vague anchors like "click here" or "read more" assert nothing; they're dead edges.
Pick two or three themes you can credibly own. For a hosting company that might be EU data privacy, WordPress performance, and migrating without downtime. Write a pillar page for each theme, then link every supporting post up to the pillar and across to its siblings using anchor text that names the relationship. Copy this pattern today: from a post titled "Cutting WordPress TTFB" link up to the pillar with the anchor WordPress performance guide, and sideways to a sibling with reduce database query time. Each anchor becomes a labelled edge tying your entity to a queryable concept.
Keep the facts consistent across the cluster and cite reputable outside sources within the content. When several pages under your domain state the same clear claims and the same figures — and outside references back them up — you're building exactly the corroboration GraphRAG rewards before it dares quote you. Depth beats breadth here: three subjects covered thoroughly will out-cite fifteen covered thinly.
A realistic 30-day plan
You don't need a big budget — you need consistency and a month of focused effort. Do it in this order because each step makes the next one stronger.
- Week 1: Audit and fix NAP and identity facts across your top mentions. One canonical version of everything.
- Week 2: Rewrite the About page with plain factual sentences up top. Add Organization schema with a full sameAs array.
- Week 3: Pick your topics and map a pillar-and-cluster structure. Publish or refresh the pillar pages.
- Week 4: Add supporting posts, wire up descriptive internal links, validate all structured data, and claim a Wikidata entry.
If part of that plan is a move to hosting that won't fight you on speed or privacy, TPC Hosting is EU-hosted and GDPR-friendly, migration is free, and you've got 30 days to back out if it isn't right. Real engineers are on support around the clock if the schema or redirects get fiddly — you won't be handed a chatbot when something breaks.
Entity-first SEO isn't a trick you apply once. It's the habit of being unmistakably, consistently one thing across the whole web — which, conveniently, is also just good business.
FAQ
What is GraphRAG in simple terms?
GraphRAG is a way AI search organises knowledge into a graph of entities and the relationships between them, then reasons over that graph to answer questions. Instead of matching keywords to documents, it looks up facts attached to known entities and cites the sources that corroborate them.
How do I know if my business is a recognised entity?
Ask a major AI assistant to describe your business by name and see whether it gets the facts right. If it hedges, confuses you with someone else, or invents details, your entity is unclear and you need to fix consistency across your site, profiles and structured data.
Is structured data enough to get cited by AI search?
No — structured data is necessary but not sufficient. It tells machines the facts you want attached to your entity, but you also need consistent identity details everywhere and genuine topical depth so independent sources corroborate what your markup claims.
Does a small business really stand a chance against big brands here?
Yes, often a better one. Entity consistency is tedious work that large brands frequently get wrong across sprawling sites, while a focused small business can enforce one clean set of facts and own two or three subjects thoroughly.
Should I add my business to Wikidata?
Yes, if you can meet its notability guidelines, because it gives AI systems a free public reference to anchor your entity to. Sign in at wikidata.org, create a new item with a few sourced statements, then link it via the sameAs property in your Organization schema so scattered mentions merge into one strong node.
