The AI answers about your field every day. Does it speak about you accurately?
Press, congresses, societies and institutions consult ChatGPT, Gemini and Claude to find out who the reference in a subspecialty is. If your entity is not disambiguated, your credentials and your research may be attributed to someone else.
This is not about acquiring patients. It is about the information on you being correct.
This page does not talk about attracting patients — advertising in healthcare is regulated, and we respect that. It talks about something else: what language models state about your training, your practice and your scientific output.
Being on Google is not the same as being in the AI’s answer.
You may hold a specialist title, board certification, indexed publications and decades of practice — and the artificial intelligence may still confuse you with a namesake, anchor you to a service you left, or credit someone else with work that is yours. Among peers, your track record is known. For the language model, it has to be structured in order to exist.
Sumaúma AI Presence makes the AIs describe your practice with precision and integrity.
This is not advertising, and nothing we do touches clinical merit. It is about structuring verifiable data — name, credentials, board certification, societies, institutions, line of scientific work and domain topics — so that language models can describe you correctly. That is what we call Presence Engineering for Generative AIs, applied to the integrity of the information about you.
We monitor
We measure your G-SoV (Generative Share of Voice) with AI-Scan and monitor what the models state about you and your field: in which topics you appear, how accurately, and whether there is incorrect information to correct.
We structure
We build your knowledge graph and tie together the nodes of your identity — credentials, certifications, societies, institutions and publications — so the AIs recognise a single, current entity and do not split your track record between namesakes.
We clone
We extract your Linguistic DNA and vectorise your line of work and the concepts you developed, so the AIs know what is yours and credit it to you.
We propagate
We publish consistent, original semantic content across authority and science-communication channels, within the ethical limits of your profession, to influence the AIs where they are trained.
Sumaúma started in 2022 as a digital marketing agency and had — and still has — the segment of professionals whose authorial work is the asset as its main vertical. We have served more than 100 of them. Today we apply that experience to the new frontier: the accuracy of what generative AIs state about who holds authority on a topic.
Questions answered.
I am a physician. How do I get the AIs to describe my practice correctly?
The first step is to measure. AI-Scan shows what the models already state about you: in which topics you appear, how accurately, and whether there is confusion with namesakes, misattributed credentials or anchoring to an old affiliation. From there, we disambiguate your entity in the knowledge graphs — tying credentials, certifications, societies, institutions and publications into a single, verifiable node; we vectorise your line of work; and we propagate content within the ethical limits of the profession. There is no shortcut and no space for sale: the AIs describe well whoever they can recognise.
Does this breach medical advertising rules?
No, because this is not advertising in the sense the rules restrain. We make no promise of results, no claims of superiority, no presentation of a technique as exclusive, and we use no patient testimonials or before-and-after imagery. What we structure is verifiable professional-identity and scientific-output data — credentials, certifications, societies, affiliations, publications — so that the information circulating about you is correct. Every piece is checked against what your professional council allows, and the limit is always yours.
The AI is associating my name with incorrect information about my training. Can that be fixed?
It can, and that is exactly the entity-disambiguation work. The model gets it wrong when it has no stable identifier tying name, credentials and institutional affiliation together. Once your professional registration, your societies, your institutions and your publications point coherently to the same entity, marked up in structured data, the description converges on what is verifiable.
Does this apply to dentists, psychologists, nutritionists and other health professions?
It does, with the same discipline. Each professional council has its own advertising code, and the work adjusts to it. The core is the same across all of them: structuring professional identity, credentials and output as verifiable data, so the models stop inferring and start describing.
How long until the information about me becomes accurate in the AIs?
Entity disambiguation is usually the fastest change to feel: as soon as credentials, certifications, societies and affiliations point to a single, verifiable node, the model stops inferring and starts describing. AI-Scan gives you the immediate diagnosis, and propagation, within the ethical limits of the profession, moves your G-SoV over the following weeks, with continuous monitoring.
Secure the accuracy of the information about you in generative AIs with Sumaúma AI Presence.
Request your AI-Scan and find out what the AIs state today about your training, your practice and your research.