AI search & growth for medical practices

Patients ask AI before they ask a doctor. Be the practice in the answer.

Healthcare leads AI-recommendation adoption — patients ask engines about symptoms, treatments, and who to see, in that order. Practices visible at that moment win the patient for years. We build compliant visibility, reputation, and intake systems for independent practices.

Published pricingMonth-to-monthYou own everything
AI answer · live ChatGPT
Which knee specialist should I see in Tampa?
01 [Your business] Recommended
02A competitor
03Another competitor

Illustrative preview — the goal of every engagement, not a promise of placement.

The problem

Why good medical practices lose to worse ones online.

01

The referral is now verified

Even doctor-referred patients check reviews and ask AI before booking — weak signals tax every referral you receive.

02

Phone-based intake leaks patients

Hold music and callback promises lose patients to whoever offers online booking — convenience is a clinical differentiator now.

03

Health systems dominate by default

Hospital-owned practices inherit domain authority. Independents must earn visibility deliberately or disappear behind them.

Your market, measured

Patients have already moved.

45%

of consumers now use AI tools to find local businesses — up from 6% a year ago.

BrightLocal, 2026
1.2%

of local businesses ever get recommended by ChatGPT across 350K+ analyzed locations.

SOCi Index, 2026
100%

of Perplexity’s local answers consult reviews — reputation is now retrieval infrastructure.

Engine behavior studies, 2026
What you get

The whole growth system, built for medical practices.

One accountable team runs everything below — you run the business.

Visibility

Practice AEO & local SEO

Provider and location data reconciled and optimized for condition, treatment, and ‘near me’ intent.

Reputation

Compliant review systems

Automated, guideline-respecting review requests building the steady profile engines weigh heavily in healthcare.

Intake

Booking & recall automation

Online scheduling, reminders, and recall sequences — fewer no-shows, fuller panels, no extra staff.

Authority

Condition & treatment content

Careful, answer-first patient education mapped to what your market asks engines — reviewed before publishing.

Website

A site that reassures

Clear providers, insurance, and booking — built to lower the barrier between symptom and appointment.

Proof

Answer Share reporting

How often engines surface your practice for your specialties in your market.

How engines actually decide

The Recommendation Stack™.

Five signal layers decide who AI engines name. Every engagement builds them in order — tap a layer to see the work behind it.

Layer 1 is the foundation — nothing above it works if the base disagrees with itself.

Know where you stand

The 5 Stages of AI Visibility.

Every business sits on exactly one rung right now. Which one decides what to fix first — and roughly 99% are stuck below Stage 4.

STAGE 112%

Invisible

Engines can’t confirm you exist. Data missing, wrong, or contradicting itself.

STAGE 234%

Indexed

You exist to the machines, but you’re never chosen. In the data, absent from the answer.

STAGE 356%

Mentioned

You surface occasionally — usually in lists, rarely as the recommendation.

STAGE 478%

Recommended

Engines actively name you in your market. This is where the phone changes.

STAGE 596%

Default Answer

First name, consistently, across engines. The position competitors can’t buy overnight.

Proof — coming soon

This is where the receipts go.

Every testimonial and result on this site will come from a real, verifiable client — named, with permission. Until we have them, this space says so out loud rather than borrowing someone else’s words.

[PLACEHOLDER · client quote]

“Replace with a real client quote once results land — ideally naming the outcome (‘AI started recommending us in 11 weeks’) and the person, business, and city.”

— Name, Role · Business, City

[PLACEHOLDER · result card]

Replace with a real, measured result: starting Answer Share → current Answer Share, over a stated number of weeks, for a named client who approved it.

Never publish a number we can’t evidence.

[PLACEHOLDER · case study]

Replace with a short case study: the situation, what we changed across the Recommendation Stack™, and what happened — including anything that didn’t work.

Link to the full write-up when it exists.

Delete this entire section once real proof replaces it — an empty promise is worse than no section.

The rules that never change

Six promises — all checkable
before you pay us a dollar.

01

Published pricing

Every price on the page. No quote calls, no setup-fee ambush.

02

Month-to-month

No contracts. We re-earn the business every single month.

03

You own everything

Site, domain, content, data, CRM — in writing, from day one.

04

Free audit, no strings

A real human review, yours to keep whether you hire us or not.

05

Honest timelines

Visibility compounds over 8–12+ weeks. We say so before you buy.

06

We name what didn’t work

Every report lists the misses. Trust is built in the down months.

The difference

Same industry. Opposite rules.

How it works
Typical provider
AnswerStack
Pricing
“Custom quote” after a discovery call
Published on the site. All of it.
Contract
12–24 months, auto-renewing
Month-to-month. Always.
Your website
Theirs. Leave and it disappears.
Yours in writing, from day one.
Reporting
40 pages of impressions
Answer Share + leads, on one screen.
AI strategy
None — 88% have no plan
The entire point of the company.

Find out where you stand before you spend a dollar.

The free audit shows your Answer Share, your visibility stage, and your first three fixes — yours to keep either way.

Straight answers

Questions owners actually ask.

Conservatively. Patient-education content is answer-first but restrained — informational, sourced, and structured for your clinical review before anything publishes. We build authority without playing doctor.

Both — specialists often see faster wins because condition-specific intent (‘knee replacement surgeon near me’) is rich, specific, and barely contested in most markets.

No. Our systems run on marketing-side data — inquiries, bookings, reviews — and never touch clinical records. Your compliance reviewer is welcome under the hood.