AI visibility · GEO · AEO · AI search optimization

AI visibility, done for you.

You run the business. We make sure AI knows why to recommend it.

See where you stand

Start with the Recommendation Check. See what AI understands about your brand, where locations or products are being blurred, and who it recommends instead.

Plain definitions

The words buyers search. The work behind them.

AI visibilityWhether the machines name you

AI visibility is whether AI assistants mention, describe, and recommend your business. It moves independently of rankings.

GEOGenerative engine optimization

GEO means making your expertise verifiable enough that AI names you inside its answer, not just ranks your page in a list.

AEOAnswer engine optimization

The same discipline pointed at answer engines: structuring what you know so the systems that answer questions directly can quote you, cite you and hand you the recommendation.

The new buying conversation

Buyers don't type keywords. They talk.

People talk to their AI assistant differently than they ever typed into a search box, because the assistant already knows them: where they work, how they eat, what laptop is on their desk.

On the way home
What's something healthy for dinner I can grab on the way home?
AI
You drive right past Verde Bowls on Route 12. Their harvest bowl fits how you've been eating, and they're open until 9.
Nobody typed "restaurants near me."

No cuisine, no neighborhood, no "near me." The assistant already knows the commute and fills all of that in. If AI cannot verify what your location on that route serves and who it suits, the recommendation goes to the brand it can verify.

The question arrives already loaded with context a search box never had, so the answer comes back as one or two names instead of ten links. The recommendation is assembled in the moment, from whatever AI can verify about the specific location on that route or the store nearest that customer. Generic brand visibility does not survive that moment. Specific, verifiable answers do.

What earns a recommendation

AI recommends businesses it can verify (foundation), that others vouch for (validation), and that know something it doesn't (information gain). We build all three.

Foundation An identity AI can resolve

The brand, every location and every relevant product line agree with each other everywhere the machines check.

Validation Proof beyond your own claims

Reviews, client evidence, credentials and third-party references AI can verify without taking your word for it.

Information gain Judgment only you can provide

The answers your teams give every day, on the record before the buyer thinks to ask the question.

That rule does not change at scale. It simply has to hold for every location and every category you want recommended, which is exactly what infrastructure is for.

The service, in plain English

What "done for you" means.

SEO. Expertise publishing. Listings. PR. Technical authority. AI recommendation intelligence. All done for you.

Knowledge entries12 Knowledge Entries per month. Firm.

Anything above 12 is over-delivery: a gift, never a promise. Inside them, 60 to 70 high-intent answers per month.

QualityThe Integrity Gate

Every entry is scored 0-100 through the Integrity Gate: nothing publishes under 80.

MeasurementThe monthly probe

A monthly visibility probe across 5 AI engines (ChatGPT, Gemini, Perplexity, Claude, Grok) with named-competitor extraction, plus the monthly branded report.

The promise boundaryReadiness, not causation

We make a business easier for AI to verify, trust, and recommend. We never promise what a model will do.

Across tracked client work

This is already producing measurable movement.

📈95%
appear in AI recommendations within 30 days
📬86%
receive AI-attributed inquiries within 90 days
🔍+22,400%
Google Search impressions in three months, from 39 to 8,800
14×
more inquiries for one client
💰$3.6M
in monthly sales from AI-referred buyers, reported by one client

Selected results across different client engagements and measurement periods, not one cohort. Individual outcomes vary, and measurement notes for each figure are available on request. See sources and measurement notes.

Fair questions

The things brand teams ask first

How is this different from local SEO or ecommerce SEO?
Good SEO remains valuable, and this work builds on it rather than replacing it. SEO helps your pages rank in a list of results. AI search optimization, sometimes called GEO (generative engine optimization) or AEO (answer engine optimization), prepares your business for a different moment: the one where the buyer asks ChatGPT, Gemini or Perplexity to do the comparing, and the answer is a recommendation rather than a list. That moment needs clear entities, verifiable evidence and decision context, which is what the infrastructure supplies. The two disciplines share foundations, and the work can sit alongside a capable SEO partner with clear responsibilities.
Can you guarantee AI will recommend us?
No, and you should be wary of anyone who says yes. We never promise what a model will do. What we promise is readiness: we make a business easier for AI to verify, trust and recommend, then we test it honestly by asking the same buyer questions on a schedule and saving the answers word for word, so you can see exactly what changed and when.
Do we need to rebuild our website or replatform?
No. The infrastructure is built on the site and systems you already have. For a multi-location brand that usually means bringing order to the location pages and business facts that already exist. For a retailer it means bringing the same order to your store locations and the business facts customers ask about. No replatforming, no rebuild.
We have hundreds of locations. Where would you even start?
Not with all of them. We start with a pilot: one market or a handful of locations. The pilot proves the model against saved before-and-after answers, and what works becomes the template for the rest of the network. You commit to a wedge, not the whole map.
Our brand facts live in a dozen systems. Is that a problem?
It is the normal starting condition, and it is exactly what the entity and data architecture work is for. Store locators, listing services and franchisee microsites tend to drift apart over time, and AI notices disagreement even when customers do not. We reconcile the facts once, structure them properly, and keep them agreeing, so that buyers and AI stop finding three different versions of your company.
Can this work with our existing agency or internal team?
Yes. Probably Genius does not need to replace the people already managing your website, SEO or location systems. We define the recommendation model, the evidence structure, the content requirements and the measurement system, then work with the people who already know how your stack operates. The aim is not to build another silo. It is to make the existing ones tell the same story.
What does success look like?
It begins with clarity. You know which recommendation questions matter, what AI currently says, where the evidence breaks and which locations are being overlooked. From there we track whether the brand becomes more accurately understood, more consistently surfaced and easier for AI to compare and recommend. The pilot establishes what is actually movable before a rollout compounds it.
Related reading

Go deeper

How does ChatGPT decide who to recommend? How much does AI visibility optimization cost? What is generative engine optimization (GEO)? What is AI reputation management?

Find out where AI is overlooking your brand.

Start with the Recommendation Check, our 109-point AI visibility diagnostic. We examine:

what AI understands about the brand
whether it can distinguish your locations or products
which facts and claims it cannot verify
where the evidence breaks across systems
which competitors it recommends instead
and where the most commercially useful opportunity sits

It is free, takes about an hour to present and carries no obligation.

See where you stand

You run the business. We make sure AI knows why to recommend it.