Know how AI describes your brand.

Buyers now ask an assistant before they ask a search box. Whatever those systems say about you is your first impression, and most brands have never once checked what it is.

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What you get

  • Prompt set covering discovery, comparison and validation questions
  • Recorded answers and named sources across major assistants
  • Share of mention against your closest competitors
  • Fixes for wrong or outdated facts models repeat about you
  • Entity consistency across site, schema and external profiles

Where it goes wrong

The problem

Assistants confidently repeat outdated pricing, wrong service descriptions and competitor names. Without a baseline you cannot tell whether that is happening, let alone whether anything you changed improved it.

What we change

We record what the major assistants say today across a fixed prompt set, correct the entity and content signals feeding those answers, then re-test monthly so progress is observed rather than assumed.

What AI visibility covers

Prompt baseline

A fixed set of discovery, comparison and validation questions, run across the major assistants and recorded verbatim.

Share of mention

How often you are named against your closest competitors, tracked over time on the same questions.

Accuracy correction

Wrong or stale facts about your business identified, then fixed at the sources those answers draw from.

Entity consistency

One name, one description, one service list across your site, schema and third-party profiles so systems resolve you confidently.

Answer gap pages

Questions where no one owns a clear answer, turned into pages structured to be retrieved and quoted.

Monthly drift tracking

Models change. Re-running the same prompts catches regressions early instead of six months later.

How we work

  1. Baseline

    We build the prompt set from your real buyer questions, run it across the major assistants and record every answer and cited source.

  2. Diagnose

    We trace where inaccurate or missing information comes from, whether that is your own site, a stale profile or a third-party page.

  3. Correct

    Entity signals are aligned, weak pages are restructured answer-first, and new pages are built for the gaps worth owning.

  4. Re-Test

    The same prompt set runs monthly. You get the answers side by side with the previous month and a short note on what changed.

What you get

We measure how AI summaries present your brand, correct what's wrong at the source, then keep watching as models update.

Visibility baseline

  • Prompt set covering discovery, comparison and validation questions
  • Recorded answers and named sources across major assistants
  • Share of mention against your closest competitors

Correction work

  • Fixes for wrong or outdated facts models repeat about you
  • Entity consistency across site, schema and external profiles
  • Pages built for the questions where nobody owns the answer

Ongoing watch

  • Monthly re-testing of the same prompts for drift
  • Alerts when an assistant states something inaccurate
  • Roadmap updated from what the testing actually shows

How we differ

AreaTypical approachOur approach
DefinitionVague AI visibility scoreRecorded answers you can read
AccuracyIgnoredWrong facts about you tracked and corrected
ScopeOne assistantChatGPT, Perplexity, Gemini and AI Overviews
CadenceOne-offMonthly re-test of a fixed prompt set

Fit check

AI visibility work suits brands already losing attention to summaries above the results. It can't promise a fixed score.

A good fit if

  • Brands losing clicks to AI summaries above the results
  • Teams that need to know how assistants describe them
  • Businesses with facts, pricing or data worth being quoted on

Probably not for

  • Anyone expecting a visibility score with a guaranteed number
  • Sites with no unique information to be cited for

Questions

How often and how accurately AI assistants mention, describe and cite your brand when people ask questions in your category. It is measured by testing real prompts, not by a single score.

No, and anyone who does is guessing. Answers vary by phrasing, account and model version. We improve the probability by fixing the signals those systems rely on, and we show the evidence either way.

ChatGPT, Perplexity, Gemini and Google AI Overviews as standard. Others can be added if your audience uses them.

By correcting it at the source: your own pages and schema first, then third-party profiles, directories and any outdated content still circulating.

It overlaps heavily. Crawlability, entity clarity and clear content help both ranked results and generative answers, which is why we run them as one programme.

Entity and factual corrections can appear within weeks once the sources update. Broader share of mention shifts over months alongside content work.

See what assistants say about you

Send us three questions your buyers ask and we will show you the answers the major assistants give today.