Capabilities
Why are competitors recommended instead of you?
Be recommended.
Become one of the brands AI systems mention, cite and recommend when your customers ask what to choose.
More and more questions no longer end with a list of links. They end with an answer naming a handful of brands. If yours is not among them you will not see it in any analytics tool: no impressions, no position, no logs. The channel exists and is invisible at the same time.
We start with measurement - real prompts sent to real models, repeated over time, split by market. Only then do we say what to do about it: what the model knows about you, where it learned it, and what is missing before it treats you as an answer.
What it covers
- AI visibility measurement across ChatGPT, Gemini, Claude, Perplexity and Google AI experiences
- Prompt universe: the questions your customers actually ask models
- AI Share of Voice against the competitors models see, not the ones you list
- Citation and source analysis - which publishers models read in your category
- Entity and brand clarity, so a model knows what you are
- Content built to be quotable in a single paragraph
Capabilities
- AI Visibility AuditFind out when AI recommends you, when it recommends your competitors - and why.
- GEOGenerative Engine Optimization: the work that makes your content usable as an answer.
- LLM OptimizationMake your site readable, retrievable and safe to quote for language models.
- AI Brand MonitoringContinuous measurement of what models say about you, in which context and on what basis.
- Entity OptimizationRemove every doubt about what your brand is, what it does and what it is connected to.
How it works
01
The first measurement also tells us who you are to the models
We start with real prompts sent to five engines. The first run says more than how you score - it says which names models use for you at all. Name variants cannot be established in theory; they have to be seen in the answers.
02
Break down what the model knows and where it learned it
For every mention we check context, sentiment and the sources the model used. That tells us whether the problem sits on your site or in the fact that models read a handful of publishers in your category and you are on none of them.
03
Work on citability
Structure that answers the question in one paragraph, unambiguous facts, consistent numbers, structured data. A model will not quote text where it has to guess the meaning.
04
Get into the sources models treat as evidence
This part runs with Digital PR and it is usually the part that actually moves the result, because models repeat what they read elsewhere more often than what a brand writes about itself.
What we measure
- Share of answers you appear in, against competitors
- Citations of your domain inside answers
- Sentiment and the context you are mentioned in
- General visibility kept strictly separate from brand-prompt visibility
From our own research
A prompt containing the brand name lifts the score without any work
In our test a fictional brand scored 36% AI visibility. Broken down, every mention came from prompts where its name had already appeared - the model was repeating it in order to say it knew nothing about it. Separated: 0% general visibility, 90% brand visibility. That is why we count the two apart. A metric you can raise by adding prompts with your own name in them is not fit to report to a board.