Category · Category Creation

Your buyer asks ChatGPT. You are invisible.

Your next customer no longer starts on Google. They ask an AI who the best option is, it names three companies, you are not one of them, and you never even knew the evaluation happened.

What is actually broken.

We increasingly get called by companies who rank well on Google and cannot understand why pipeline is softening. The reason is that the first search has moved. A growing share of buyers now open ChatGPT or Perplexity, ask who the best option is, and shortlist from the answer. If the model does not name you, you are not in the running, and unlike a search result, there is no page two to be found on.

What makes this dangerous is that it is invisible. The evaluation happens inside a conversation you never see. There is no referrer in your analytics, no lost-deal note, no signal that you were left off a list. You simply feel demand cooling and blame the wrong thing.

The deeper problem is that being named by an AI is a different craft from ranking on Google, and almost no one has built for it yet. Your hard-won search position does not carry over. The models draw on a different mix of signals, and if no one has shaped those signals for you, the answer defaults to whoever the model happened to learn about.

Why it blocks scale.

When the AI answer becomes the shortlist, being absent from it silently caps your pipeline at the top. You never get to compete on product or price, because you were filtered out before the buyer reached your site. The deals you lose this way do not show up as losses. They show up as demand that quietly never arrives.

The cost compounds because this surface is winner-takes-most and moving fast. The companies named early become the examples the models keep reaching for, which makes them more likely to be named again. Every quarter you wait, the default answers harden around whoever showed up first, and the position gets more expensive to take.

Our view.

Buyers now start research inside AI answer engines, and they trust the recommendation because it arrives as a synthesised, neutral-sounding answer rather than an ad. That trust is why AI-referred visitors tend to arrive far warmer than a cold search click, they have already been pre-sold by the model. Being in the answer is closer to a referral than to a ranking.

You cannot control what a model says, but you can shape it. Answer engines assemble their responses from content, structure, and third-party mentions, and all three are buildable. The work is to become the well-structured, widely-referenced, clearly-positioned option the model has every reason to name, on the specific questions your buyers ask.

The system.

We do not chase a ranking. We build for the answer: the content, structure, and third-party presence that give the engines a reason to name you on the questions your buyers ask.

A map of the AI conversation

We find the exact questions your buyers ask the models, and see who gets named, on what, and why. You cannot fix a market you cannot see.

Answers the models cite

The content and structured data built the way answer engines consume it, so your positioning is available in the form the model can lift into its response.

Third-party presence

The models weigh what others say about you. We build the reviews, mentions, and reference points across the sources they draw from, so your name shows up beyond your own site.

A machine-readable position

We sharpen how you are described so the model can place you confidently, on the use cases you win, instead of guessing or leaving you out.

Tracking and defense

We monitor citations across ChatGPT, Perplexity, and AI Overviews, hold the questions you win, and keep pushing on the ones you should own but do not yet.

The build, step by step.

01
See what the engines say

We map the buyer’s AI questions and benchmark today’s answers, so we know exactly which ones you are missing from, and why.

02
Build the signals

We ship the content, structure, and third-party presence that give the models a reason to name you, starting with the questions closest to a buying decision.

03
Earn the citations

We work the sources the models trust until your name starts appearing in the answers, and confirm it against live queries.

04
Hold and hand over

We track the questions you win, defend them, and leave you a repeatable system and a map of where to keep pushing.

The logic.

This works because it meets buyers on the surface where their decision now begins, and arrives with the model’s implied endorsement rather than as another ad. That is why the attention converts so much better than a cold click: the buyer has already been guided to you by a source they trust.

It works because the position is winnable right now. Almost no one has built for it, so the questions are still open, and the companies that claim them early become the defaults the models keep reaching for. Getting there first is cheap today and expensive later.

What changes
for the company.

Who this
is for.

And when we say so

We will not promise to make an AI say whatever you want. We build the content, structure, and references that give the engines a reason to name you, and we track where you win and lose. If the answer engines are not where your buyers are yet, we say so, and put the effort where they are.

This is you?

We take a cohort of 21 founders through the full 0 to 1. Applications reviewed within 5 business days.