Machines describe you
whether or not you’ve told them how.
We build the dual identity — distinctive enough for a person to remember, structured enough for a machine to get right.
The shift
One of your two audiences
can’t see your logo.
There’s a finding in creative testing that almost nobody has absorbed. When generated advertising is tested against the norms, it performs well on emotional response — often better than the average human-made ad. Most people don’t spot it. So the idea that audiences simply reject this work is not true.
But the same testing shows it consistently underperforms on distinctiveness and brand recognition — the two things that build memory over time. A model is trained to produce the middle of everything it has seen. A brand is, by definition, not the middle. Which means brand codes get more valuable as output volume rises, not less.
That’s the human half. The machine half is more immediate, and it’s usually the reason people call. Brands are finding themselves described by AI assistants using products they discontinued years ago, prices that are long gone, and positioning they abandoned. You can’t fix that inside the model. You fix it in the sources the model reads — which means your brand needs a maintained, structured, first-party account of itself.
Two audiences. Two artefacts. One strategy.
Client challenges
SOUND FAMILIAR?“An AI assistant describes us using a product we discontinued years ago.”
We find the sources it’s actually reading, correct them at origin, and maintain a fact base so there’s something current to retrieve next time. These systems don’t behave identically twice, so we track this as a trend rather than declaring it fixed and walking away.
“When AI compares us to competitors, it gets the comparison wrong.”
Comparison sets are assembled from whatever is retrievable. If your category position, your differences and your exclusions aren’t stated somewhere structured and findable, the model infers them — and it infers from whoever did bother to state theirs.
“Everything we generate looks like everything everyone generates.”
Brand codes, written as constraints rather than as a mood board. Specific, unusual, and enforceable on a system that will otherwise smooth them away. This is the part a machine structurally cannot supply for you.
“Our guidelines are a sixty-page PDF and nobody applies them at volume.”
Guidelines become machine-enforceable constraints plus a feedback loop, where every approval and every rejection teaches the system. That accumulating judgement is the real asset — and it belongs to you.
“We have no idea what a model would say about us if asked.”
We’ll show you. Sampled across the major assistants, asked enough times to mean something, with the sources each answer drew from. It tends to be an uncomfortable read and a very productive one.
What we build
Machine Perception Audit
The way in. What the major assistants actually say about you today, sampled enough times to be meaningful, with the sources behind each answer and a plain comparison against what you believe your positioning to be. Deterministic where it can be, statistical where it can’t, and always shown with the working.
Dual Identity Definition
The core deliverable. Two artefacts from one strategy: a human-facing positioning and expression system, and a machine-facing definition of who you are, what you sell, what you are not, and what you’re comparable to — written as structured, retrievable, unambiguous fact.
Distinctive Brand Codes
The specific, defensible assets — visual, verbal, sonic, structural — that a generative system must reproduce and must never average out. Written as constraints a machine can be held to.
Entity & Source Architecture
Disambiguation across the sources a model actually reads. Consistent references, structured data as hygiene, first-party fact sources, and a homepage rebuilt as a definition of the organisation rather than a brochure for it.
Narrative & Message Architecture
The message system that survives fragmentation. What still holds when your brand is being summarised in three sentences by something you don’t control.
Machine Fact Base
A maintained, structured source of truth at brand level: positioning, policies, claims, comparisons, category definition, corporate facts. The thing that stops the drift coming back.
Site & Experience Build
The brand as a working thing. Sites, product surfaces and digital experiences built to the dual standard: distinctive for a person, and structurally legible for a machine.
Where we draw lines
Three things
we won’t do here.
Encyclopaedia entries.
Paying for or writing your own entry on a community-edited reference site carries real policy and reputational risk, and it matters far less to AI answers than people assume. We’ll help you become the kind of organisation somebody writes about independently. We won’t write it ourselves.
Selling structured data as a citation lever.
It isn’t one. Structured data is genuinely useful — for disambiguation, for classic search results, for making a page parseable — and we use it for exactly that. We’d rather tell you which job it does than let you believe it does a different one.
Manufacturing mentions.
There’s a version of this work that means placing real stories, real data and real expertise where they’ll actually be read. And there’s a version that means creating mentions whose only purpose is to be counted. The test we apply: would this still be worth publishing if no model ever read it? If not, we don’t do it.
FAQ
Frequently asked
questions.
Often not. In most cases the human-facing brand is fine and the machine-facing one simply doesn’t exist. We build the missing half and tighten the codes on the existing half.
You do, and it’s in the contract. If you leave, it leaves with you — the reference sets and the accumulated approval history included. We think that should be standard. It currently isn’t.
Distinctiveness can be measured. We baseline recognition and attribution before, and re-test after. If the codes aren’t holding at volume, that’s a finding, not a failure.
Yes, and often that’s the right shape. They hold the human half. We build the machine half and make sure the two say the same thing.
Find out
what the models say about you.
Two to three weeks, fixed fee, and the sources behind every answer.