What ChatGPT knows about your brand comes from Wikidata. Is it complete?
GetCited audits your knowledge graph presence, scores your Wikidata completeness 0–100%, flags what's missing, and drafts your Wikipedia article. No other AEO tool does this.
Why the knowledge graph matters for AI.
AI engines read Wikidata first
AI engines read Wikidata to understand what your brand is, who founded it, and what category it belongs to — incomplete data means vague AI descriptions of your brand.
Wikipedia is an authority signal
Wikipedia notability signals make AI treat your brand as an authoritative source. Brands with a Wikipedia article get described in specifics; brands without one get generic filler.
Inconsistency erodes citation confidence
Inconsistencies between Wikipedia, Wikidata, and your own website reduce AI citation confidence. When the sources disagree, AI engines hedge — or skip your brand entirely.
Three checks. One entity score.
Everything AI engines use to decide what your brand is — audited, scored, and fixed from one place.
Wikidata Completeness Score + Edit Assist
Score your brand against 6 key properties. For each missing property, the platform auto-derives the correct value from your Brand Context and generates the exact Quick Statement syntax you can paste directly into Wikidata — no Wikidata expertise required.
Wikipedia Notability Check + AI Draft
GetCited assesses all four notability signals — brand mention count, Wikidata presence, Knowledge Panel detection, and domain age — before surfacing the AI-assisted Wikipedia draft. If you're not ready, you know exactly what to fix first.
Live Completeness Widget on Your Dashboard
Your Knowledge Graph completeness score appears on the main monitoring dashboard at all times — not buried in an audit tab. Green, amber, or red pill with the specific missing properties shown as tags. One click takes you straight to the fix.
The difference is what AI says when someone asks about you.
Before — incomplete knowledge graph
“Acme Co offers various software products and services.”
Vague. Interchangeable. Forgettable. The AI has nothing specific to work with.
After — complete Wikidata + Wikipedia
“Acme Co is a B2B SaaS platform founded in 2018, specialising in AEO optimisation for mid-market brands.”
Specific category, founding date, audience — pulled straight from your knowledge graph.
Who needs this.
If AI engines answer questions about your category, your knowledge graph is already part of the answer — complete or not.
Mid-market brands
You have real traction but AI engines describe you in generic terms. A complete knowledge graph is the fastest way to make ChatGPT describe your brand the way you would.
Agencies
Entity presence is the AEO deliverable no other tool automates. Run the audit per client, hand over the completeness score, and ship the Wikipedia draft as a billable asset.
Enterprise
Your knowledge graph already exists — the risk is that it's wrong or stale. Reconciliation flags every inconsistency between Wikipedia, Wikidata, and your own properties.
Find out what AI actually knows about your brand.
Get access to the platform. Run the entity audit, see your Wikidata completeness score, and get your Wikipedia draft — in minutes.