Why do AI models have different knowledge of my brand?

Each AI model — ChatGPT, Gemini, Claude — is trained on different data sets, with different cutoff dates and weighting algorithms. A brand with strong Wikipedia coverage and structured Organization schema may be well-known to Gemini (which pulls heavily from Google Knowledge Graph) but partially unknown to ChatGPT if its training data had fewer web mentions of that brand. Inconsistent knowledge across models is a signal that your entity signals are not broad or authoritative enough to penetrate multiple training corpora reliably.

How do I improve my entity coverage?

The four highest-impact actions are: (1) Add comprehensive Organization schema to your homepage and About page — include name, url, logo, description, sameAs links to your Wikipedia, Wikidata, and social profiles. (2) Create or claim a Wikipedia/Wikidata entry if your brand meets notability criteria. (3) Earn mentions and links from high-authority publications in your industry — these are the training signal sources AI models weight most heavily. (4) Ensure your brand name, description, and category are consistent across all major platforms: LinkedIn, Crunchbase, industry directories, press releases.

What does "Not Recognised" mean in the entity check?

"Not Recognised" means the AI model returned no meaningful description of your brand — it either has no entry in its training data or conflated your brand with something else. This is the highest-priority fix: brands that AI models don't recognise cannot be cited in AI-generated answers, regardless of content quality or backlink profile. The first priority is building basic entity signals: Organization schema, a Wikidata entry, and brand mentions in authoritative web sources.

What is Organization schema and why does it matter for AI?

Organization schema is a structured data markup you add to your website that explicitly declares your brand's name, type, description, URL, logo, founding date, and sameAs connections to other authoritative profiles. AI crawlers like GPTBot and Google's crawlers parse this schema to build or verify their entity knowledge of your brand. Without it, AI models must infer your brand identity from unstructured text — a less reliable process that produces incomplete or inaccurate entity descriptions.

Does Wikipedia affect AI entity recognition?

Yes — significantly. Wikipedia is one of the highest-weighted sources in the training data of most major AI models. A Wikipedia entry for your brand provides a structured, third-party-verified description that AI models rely on heavily. Wikidata (Wikipedia's structured data sibling) is equally important: it provides machine-readable entity data with explicit relationships to other entities, which AI models use to place your brand in the right conceptual context. Both are worth investing in if your brand meets notability criteria.

How long does it take to improve entity coverage after making changes?

Entity coverage changes propagate on different timelines depending on the model. Google-based systems (Gemini, Google AI Overviews) can reflect schema and Knowledge Graph updates within weeks. OpenAI models (ChatGPT) are updated on training cycles — improvements to web-based entity signals may not be reflected until the next model training update, which can take several months. Consistently building entity signals across multiple authoritative sources accelerates recognition across all platforms.

Home / Tools / Entity Coverage Checker

Entity Coverage
Checker

See exactly how ChatGPT, Claude, and Gemini describe your brand — and whether their knowledge is accurate, partial, or missing.

Definition

What Is Entity Coverage?

Direct Answer

Entity coverage is the degree to which your brand is recognised as a distinct, accurately described entity across AI knowledge systems — including ChatGPT, Gemini, Claude, Google Knowledge Graph, and Wikidata. High entity coverage means AI models can confidently describe who you are, what you do, and where you sit in your industry. Low coverage means missed citations, hallucinated descriptions, or complete invisibility in AI-generated answers.

Traditional SEO focuses on content relevance and backlink authority. AEO adds a third dimension: entity recognition. Before an AI model will cite your brand in a response, it must first recognise your brand as a known entity — with a coherent description, a category, and a relationship to other entities in your field. Without that foundation, even technically strong content may be invisible to AI-generated recommendations.

Well Known

AI model has accurate, detailed knowledge of your brand. You're eligible for citations.

Partially Known

AI has limited or slightly inaccurate information. Citations are inconsistent. Fixable.

Not Recognised

AI has no meaningful knowledge. You cannot be cited regardless of content quality.

The Problem

The Entity Problem in AI Search

AI models must recognise your brand before they can recommend it. Most brands have entity gaps they don't know exist.

AI Hallucinations About Your Brand

When AI models have incomplete entity knowledge, they sometimes fill the gap with fabricated descriptions — wrong founding dates, incorrect product descriptions, or confused associations with competitors. This misinformation circulates in AI answers to users researching your brand.

Inconsistent Recognition Across Platforms

ChatGPT may describe your brand accurately while Gemini returns nothing, or vice versa. Each platform's AI draws on different training data. Without consistent entity signals across authoritative web sources, recognition is patchy and unreliable.

Citation Blocked at the Entity Layer

Content quality alone is not enough. An AI model that doesn't recognise your brand as a trustworthy entity will skip over your citations — even if your article is the most comprehensive resource on the topic. Entity recognition is the prerequisite for citation eligibility.

// How to Use

Check Your Entity in 3 Steps

Enter Your Brand or Company Name

Type the exact name of your brand, company, person, or product as you want AI models to know it. Use the name as it appears on your official website and profiles — e.g. "Moz", "HubSpot", or your own company name.

Review Each AI Model's Knowledge

The tool queries ChatGPT and Gemini simultaneously, showing how each model describes your entity. Each result is rated as Well Known (accurate, detailed description), Partially Known (limited or slightly inaccurate), or Not Recognised (no meaningful knowledge). Look for inconsistencies between models.

Diagnose Gaps and Prioritise Fixes

"Not Recognised" requires immediate action: add Organization schema and seek authoritative brand mentions. "Partially Known" means your entity exists but needs stronger signals: more consistent descriptions across sources, a Wikidata entry, or sameAs schema linking your profiles. "Well Known" on all models means your entity foundation is solid.

// FAQ

Entity CoverageChecker