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AI Visibility
ChatGPT, Gemini, Perplexity and Google AI Overviews read a small set of high-authority sources. Brands that exist on Wikipedia and Wikidata are cited consistently. The rest are paraphrased — or skipped.
What you get
AI answer engines (ChatGPT, Gemini, Perplexity, Google AI Overviews) draw on a small set of high-authority sources. We audit your presence across Wikipedia, Wikidata, Reddit, Quora and structured media — and build the missing pieces.
Starting price
Audit from €490
Typical timeline
Ongoing
Best for
Why this is happening
LLMs are trained on the open web but answers must be defensible. When a model needs to describe a company, it leans on a small, repeated set of encyclopedic and structured sources. Brands that sit inside that set are quoted accurately. Brands outside it get paraphrased — or hallucinated.
The training layer
Foundation models like GPT-4, Claude, Gemini and Llama are pre-trained on Wikipedia and a handful of structured datasets. Wikipedia alone makes up several percent of every major model's training corpus.
The retrieval layer
ChatGPT browsing, Perplexity, Gemini grounding and Google AI Overviews query the live web. They preferentially surface Wikipedia, Wikidata, high-authority media, and structured Q&A like Reddit and Quora.
The entity layer
Behind every confident AI answer is an entity ID — usually a Wikidata Q-number. If your brand has no entity, AI systems treat you as a string of letters, not a known company.
The AI visibility ecosystem
AI answer engines read from the same set of high-authority sources humans trust. Coverage on each platform compounds — gaps on any one of them are noticeable.
Encyclopedia
160+ language editions, the most-cited reference on the open web.
Why: Heavily weighted by every major LLM. The single biggest source of brand context for AI answers.
Structured data
Open knowledge graph — entities, relationships and identifiers in machine-readable form.
Why: Feeds Google's Knowledge Graph and is read directly by LLM retrieval pipelines.
Community
Threaded discussions across thousands of communities.
Why: AI systems cite Reddit threads as 'real user opinion'. Often shown in Google Search results.
Q&A / AI answers
Q&A platform with expert long-form answers.
Why: Strong organic search ranking and direct citation by AI answer engines.
Structured data
The right-rail card on Google Search results.
Why: First impression for ~80% of branded searches. Powered by Wikipedia + Wikidata.
Q&A / AI answers
Generative AI answer engines.
Why: Where buyers increasingly research brands before clicking through to Google.
Media
Independent media that meets Wikipedia's reliable-source bar.
Why: The notability backbone. Without it, no Wikipedia page is safe from deletion.
Alt-wiki
Simpler editorial standards on the same Wikipedia infrastructure.
Why: Easier publication path that still inherits Wikipedia's domain authority.
How an engagement runs
Step 1
We query the major LLMs about your brand, your competitors, and the questions your buyers ask. We map what's said today and where the gaps are.
Step 2
Based on the audit we propose a coordinated plan — Wikipedia, Wikidata, Reddit, Quora, structured media — sequenced to compound.
Step 3
We execute across platforms, with a single project lead. Every step is source-first and policy-compliant.
Step 4
Monthly checks across the major LLMs. We report how brand mentions evolve and surface emerging risks early.
What the audit covers
What we do not promise
The companies pitching 'AI manipulation' are selling a fantasy. AI answer engines aren't a search algorithm you game — they're language models reading the open web. Here's the truth about what we can and cannot do.
We do not
Inject content into ChatGPT or any other model. Their training and retrieval pipelines are not for sale.
We do not
Guarantee that your brand will appear in a specific AI answer. Model providers control their own retrieval logic and grounding.
We do
Build the reliable, neutral, source-verified presence that materially raises the probability of accurate AI mentions — and lets you track whether that probability is going up over time.
Frequently asked questions
A 3-5 day audit gives you a baseline — and a plan to fix the gaps.