For mentors and executive coaches

In a crowded market, the AI answers with three names. Is one of them yours?

Executives, HR teams and boards use ChatGPT, Gemini and Claude to find and validate who to work with. In a market where almost everyone describes themselves the same way, the AI recommends whoever it can tell apart.

The decision moved

The AI became the filter for a market that had no filter.

Anyone can get a certification. Everyone has a sales page. What the artificial intelligence can actually distinguish is who has a method with a name, an author and a trail.

Example of a question to the AIs
"Who is the best mentor for a CEO scaling the company?"
— An executive searching on their own
Example of a question to the AIs
"Does mentor [name] have a proprietary method? What results have they delivered?"
— HR validating a referral
Example of a question to the AIs
"Which executive mentoring methodologies actually work?"
— The AI defining what counts as serious in your market
The cost of being invisible to the AIs

Being on Google is not the same as being in the AI’s answer.

You may have solid training, high-level clients and results your mentees vouch for — and the artificial intelligence may still describe you exactly as it describes two hundred others. When everything sounds the same, the model picks what it can explain with confidence. And what it explains with confidence is a method with authorship, not a promise of transformation.

Three names
is the length of the list the AI returns in a market with thousands of professionals.
Zero differentiation
is what the model sees when your method has no name, no author and no public trail.
One question
separates who gets considered from who never even comes up.
The solution

Sumaúma AI Presence turns your method into something the AIs recognise and recommend.

This is not about charging more or changing your approach. It is about structuring what is already yours — name, method, track record, training and results — so that language models can reliably understand who you are and why they should recommend you instead of anyone else. That is what we call Presence Engineering for Generative AIs, applied to what sets you apart as a mentor.

Pillar 01

We monitor

We measure your G-SoV (Generative Share of Voice) with AI-Scan: how present your name is in the answers about mentoring and leadership development in your topics, across several AI models.

Pillar 02

We structure

We build your knowledge graph and the nodes of your identity, so the AIs recognise you as a reliable entity and do not confuse you with namesakes or with the school where you trained.

Pillar 03

We clone

We extract your Linguistic DNA and vectorise your own method — the concepts you named, the stages you designed — so the AIs know what is yours and credit it to you.

Pillar 04

We propagate

We publish consistent, original semantic content across the authority channels of the corporate market, to influence the AIs where they are trained.

+100
professionals served since 2022
We come from the market of those who live off their own name

Sumaúma started in 2022 as a digital marketing agency and had — and still has — the corporate speakers and business consultants segment as its main vertical. We have served more than 100 professionals from that universe. Today we apply that experience to the new frontier: your presence in the answers of generative AIs.

Frequently asked questions

Questions answered.

I am an executive mentor. How do I show up in the answers of generative AIs?

The first step is to measure. AI-Scan shows whether the AIs already cite your name in your mentoring topics, in what position, and who they credit for your method. From there, we structure your entities in the knowledge graphs so the models reliably recognise who you are; we extract your Linguistic DNA and vectorise your method, so what circulates about your work is credited to you; and we propagate original content across the channels the AIs are trained on. There is no shortcut and no space for sale: the AIs recommend whoever they can recognise.

How do I stand out in the AI in a market where everyone says the same thing?

By structuring what most people do not have: a method with its own name, declared authorship and a public trail. Language models recommend entities they can describe with confidence — and they cannot describe "leadership transformation", because that distinguishes no one. Once your method has a name, named stages, a dense and consistent body of content and a track record tied to it, the model finally has something to say about you specifically.

Do international certifications help the AI recommend me?

They help when they are structured as data, not just as a badge in an image. A credential that appears only in your site footer is invisible to the model. The same credential marked up in structured data, linked to the issuing institution and consistent across your site, your profile and the sources that mention you, becomes an attribute the model can cite. The difference is not having it — it is being legible.

Does this replace my referral network?

No — it complements it. Referral remains the strongest channel in mentoring. Presence Engineering takes care of what happens around it: when a referral arrives, the person who received it will check your name in the AI. That answer is what we are taking care of.

How long until the AI includes me in the list when people ask for a mentor?

It is not immediate, and it is not a button we switch on or off. AI-Scan shows you your position today; giving your method a name and an author is usually the first noticeable change, because that is what lifts you out of the generic pile and gives the model something specific to say; and propagation moves your G-SoV over the following weeks, with continuous monitoring.

Make your method recognisable and recommendable in generative AIs with Sumaúma AI Presence.

Request your AI-Scan and find out how the AIs describe you today — and who they credit for your method.