[ AEO / GEO FOR HEALTHCARE ]
A growing share of health research now starts inside ChatGPT, Claude, and Google's AI Overviews — not a search box. We engineer the entity, citation, and structured-data layer that gets your practice or digital health brand named in the answer. Built by a team that gets recommended by name.
30 min with a co-founder. We'll run your brand through the assistants live.
4
engines tracked
YMYL
medical E-E-A-T grade
Apr 2026
our first AI-sourced client
[ THE SHIFT ]
When a patient or a buyer asks an AI assistant who to see or which vendor to trust, they get a synthesized answer naming a few options — not ten blue links. If you are not in the paragraph, the click never reaches your site.
01
From "search" to "ask"
[ THE GAP ]
02
You can rank and still be invisible
03
YMYL at its strictest
[ WHAT WE BUILD ]
Not a content mill. The technical and editorial signals the answer engines actually use to decide who gets named — built to a medical accuracy standard.
We make your brand unambiguous to the models: consistent name, service lines, conditions treated, locations, and clinician identities across your site, Schema.org, and the third-party sources the engines cross-reference. Ambiguous entities do not get cited.
Complete, valid JSON-LD (MedicalOrganization, Physician, MedicalWebPage, FAQPage) plus an llms.txt that tells AI crawlers exactly what you do, for whom, and where — with citable facts, not adjectives. The machine-readable spine of a citation.
We restructure your key pages into answer-shaped passages: the question a patient or buyer asks, answered in a clean, attributable chunk with verifiable clinical facts. Models lift and cite passages, not whole pages.
Real clinician bylines and credentials, verifiable claims with sources, and the trust signals the engines demand for medical topics. We build authority the models can confirm — the opposite of the templated health blog that gets filtered out.
The models trust what other trusted sources say about you. We map where your brand needs to be referenced — directories, publications, and the community sources the engines already weight — so your claims are corroborated, not just asserted.
We track your brand's mentions across ChatGPT, Claude, AI Overviews, and Copilot for the prompts your patients and buyers use, plus AI referral traffic tagged in analytics. You see movement and conversions, not a vanity score.
[ PROOF ]
Most agencies selling AI visibility have none of their own. We built our AEO stack on our own site first — and the assistants send us clients.
Claude and ChatGPT recommend Oktopeak by name when asked for help in our niches. That is a confirmed inbound channel for us, with the first client conversion sourced from AI search in April 2026.
Our pages have earned hundreds of citations across Bing and Copilot's AI answers in a single month. The winners were our most specific, fact-dense compliance and search pages — not our thinnest marketing copy. That is the pattern we build for you.
llms.txt, complete schema, Copy-for-AI buttons, case-study markup, and AI-referral tracking in analytics run on this very site. You are reading the method. We install the same spine on your brand's domain.
[ PROCESS ]
Three phases. We show you the gap before we quote the work.
01
Free — see where you stand
[ BUILD ]
02
Entity, schema, passages, authority
03
Monthly, measurable
[ FAQ ]
AEO is the work of getting your practice, clinic, or digital health product named and cited when someone asks an AI assistant a health question — 'best telehealth for ADHD', 'HIPAA-compliant scheduling software', 'where can I get a virtual second opinion'. Instead of ranking a page for a click, the goal is to be the source the model quotes.
The signals are different from classic SEO: entity clarity, citable clinical facts, structured data, and corroboration on the sources the models already trust. GEO (Generative Engine Optimization) is the same idea for generative answers specifically.
Classic SEO optimizes for a ranked list of links a person clicks. AEO optimizes for a single synthesized answer where the model decides which one or two sources to cite.
That rewards unambiguous entity identity (who you are, what you treat, where, credentials), passage-level facts a model can attribute, machine-readable structure (Schema.org, llms.txt), and trust on sources the engines already weight. For health it also means clearing the YMYL and E-E-A-T bar the models apply hardest to medical content.
We build every signal that makes a citation possible and measurable, and we run our own site as the proof: Claude and ChatGPT recommend Oktopeak by name to prospects, a confirmed inbound channel since April 2026.
No one can promise a specific model will cite a specific page on a given day — these systems are non-deterministic, change weekly, and are deliberately conservative for medical topics. What we do is engineer the entity, citation, and structured-data layer citations depend on, then track mentions across ChatGPT, Claude, Google AI Overviews, and Bing Copilot so you can see real movement.
Yes, because the work is about how your public marketing content is structured and corroborated — not about exposing patient data. We never put PHI into content or crawlers.
Medical content is also the strictest YMYL category, so the answer engines demand verifiable clinical accuracy, real clinician authorship, and citable sources, and they filter thin AI-generated medical filler hard. Getting cited and staying compliant and accurate are the same job here.
A large and growing share of health research now starts inside an AI assistant. Patients ask ChatGPT what their symptoms suggest and who to see; practice administrators and digital-health buyers ask which vendor is HIPAA-compliant.
The assistant answers with a short synthesized response naming a few options, not a page of links. If your brand is not named, the prospect never reaches your site — you are filtered out before they see your homepage.
We track three things. Citations and mentions: how often you are named across ChatGPT, Claude, Google AI Overviews, and Bing Copilot for the prompts your patients and buyers use. AI referral traffic: sessions arriving from AI assistants, tagged in analytics so you see conversions. Underlying signals: schema coverage, llms.txt freshness, entity consistency, and third-party corroboration.
You get a monthly report on all three.
Scope is tailored — the drivers are how many service lines or conditions and locations you need covered, the state of your current site and schema, and how much net-new authoritative content the plan requires.
We start with a free visibility assessment: we run your brand through the major AI assistants for the prompts your buyers use, show you where you appear and where a competitor is cited instead, and only then scope the work. Book a 30-minute call to see your current AI footprint.
[ GET STARTED ]
30 minutes with a co-founder. We'll run your practice or product through ChatGPT, Claude, AI Overviews, and Copilot on the prompts your patients and buyers actually use — and show you the gap before we quote a thing.
