Industries · Healthtech & Digital Health

Inhealthtech,AIvisibilityisn'tthequestion.Accuracyis.

When a patient, a clinician, or a hospital procurement lead asks an AI engine for a telehealth platform or a mental-health tool, your brand is either missing, mentioned in passing, or — most often — described inaccurately. detectabli is the AI visibility infrastructure that gets healthtech brands cited, and cited correctly.

By the numbers
of US adults use AI chatbots at least once a month to find health information0
KFF Health Misinformation Tracking Poll, Aug 2024
of those users aren't confident they can tell whether the AI's health information is accurate0
KFF Health Misinformation Tracking Poll, Aug 2024
The trust problem

AI doesn't just omit healthtech brands. It misrepresents them.

Most categories worry about being left out of an AI answer. In healthtech, the more pressing risk is being included with the wrong details — a stale care model, an outdated clinical claim, a competitor's feature attributed to your product. Patients, clinicians, and procurement teams use those summaries to form first impressions. In a regulated, trust-dependent industry, that distinction matters beyond marketing.

01

Patients

Form first impressions of care experience and credibility from a paragraph they never see you write.

02

Clinicians

Evaluate evidence, integrations, and workflow fit from AI summaries when a peer doesn't already recommend a tool.

03

Procurement

Build vendor shortlists from AI-assisted research before security review, RFP, or any conversation with sales.

01Two audiences. Two ways to be misread.
AI engines are now the first touchpoint for healthcare buyers and patients alike. The brand cited — and cited accurately — is the one that gets the demo, the download, the appointment.

How healthtech loses the consideration moment in AI search.

For B2B healthtech

Hospital systems and health plans research vendors in AI first.

When a CIO at a hospital system asks Perplexity "best patient engagement platform with EHR integration," the answer is built from your competitors' implementation case studies, KLAS references, and security posture pages — and skips yours. By the time a vendor evaluation form is shared, your category position has already been set.

  • Clinical case studies aren't structured as authority sources
  • Integration and EHR support claims aren't legible to AI engines
  • Security and HIPAA posture isn't tied to your brand entity
  • Outcome metrics are paraphrased — and frequently misattributed
For consumer digital health

Patients and caregivers form impressions before they tap install.

When a patient asks ChatGPT "best app for managing anxiety" or a caregiver searches for a chronic-care tool, AI describes the category in a few sentences. A single omission, an outdated feature description, or a misrepresented care model and your brand exits consideration silently — without a single click for you to attribute.

  • App-store positioning doesn't translate to AI-engine context
  • Clinical safety and evidence claims aren't anchored to your brand
  • Pricing, eligibility, and care-model details surface inconsistently
  • Reviews and testimonials aren't extractable as third-party validation
02Why healthtech is different.
What's actually changing under the hood

Three forces shaping how healthcare buyers actually find you now.

AI is the first touchpoint — for patients and procurement.

Both consumer and B2B healthcare buyers now reach an AI engine before they reach you. The decision moves up-funnel, into a conversation you don't see and don't shape unless you've explicitly built for it.

Trust signals are weighted heavier here than anywhere else.

AI engines weight clinical references, regulatory mentions, and third-party validation more heavily for health categories than nearly any other vertical. If those signals aren't tied to your brand, you don't enter the answer at all.

Early movers are hardest to displace.

AI categorisation in healthtech is consolidating quickly. Brands establishing visibility — and accurate descriptions — now compound an advantage that gets meaningfully harder to reverse with every model retraining cycle.

03How detectabli works for healthtech
A repeatable system tuned to digital-health category conventions, clinical and regulatory references, and the way AI engines weight trust signals across patient and procurement research.

From invisible — and inaccurate — to correctly cited, in four steps.

Audit

We run 600+ AI-engine queries across your product categories, competitor set, and patient + clinician intent terms to map exactly where you're cited, mis-cited, or missing entirely.

  • Per-engine visibility score
  • Factual-accuracy + hallucination log
  • Competitor citation share

Identify Gaps

We pinpoint the entity, schema, and authority signals AI engines need from you — and the specific factual misstatements quietly circulating about your product today.

  • Entity-clarity gap report
  • Mis-citation + hallucination inventory
  • Trust-signal coverage benchmarking

Optimize

Our team rewrites and restructures your highest-leverage assets — product pages, clinical case studies, security posture, support docs — so AI engines extract you with the right facts and the right framing.

  • Citation-ready, evidence-anchored rewrites
  • Schema deploy via single-line embed
  • Authority-source backlink targeting

Monitor

Live dashboards track every AI-engine citation, sentiment shift, factual drift, and competitor change — with alerts the moment a hallucination or mis-citation appears.

  • Real-time citation feed
  • Hallucination + accuracy drift alerts
  • Quarterly executive readout
AI Visibility Score+19 this quarter
[Your platform]0
ChatGPTChatGPT
↗ +140
PerplexityPerplexity
↗ +210
GeminiGemini
↗ +90
ClaudeClaude
↗ +130
GrokGrok
↘ -20
DeepSeek
↗ +50
Visibility vs accuracy

Getting cited is half the work. Getting cited correctly is the rest.

In most categories, the goal of AI visibility work is more citations. In healthtech, the goal is correct citations. detectabli was built for the difference: we measure not just whether AI engines mention your product, but how — pricing, care model, evidence, integrations, regulatory posture — and surface drift the moment it appears.

Visibility-only programs
  • Track whether your brand is mentioned
  • Optimize for citation count
  • Measure share of voice over time
  • Flag when competitors get cited
Accuracy-first AI visibility · detectabli
  • Track exactly how each AI engine describes your product
  • Detect factual drift on pricing, features, and clinical claims
  • Alert on mis-citations the moment they appear in any engine
  • Correct hallucinations at the source so they don't repeat
04Coverage
One unified score across the engines that actually shape healthcare and digital-health buying decisions. No blind spots, no engine-specific guesswork.

The six AI engines we monitor — every query, every day.

EngineCoverage
ChatGPTChatGPTPatient + clinician research
PerplexityPerplexityVendor + comparison queries
GeminiGeminiWorkspace + Google AI Overviews
ClaudeClaudeLong-form analysis + clinical memos
GrokGrokReal-time market + regulatory pulse
DeepSeekEmerging APAC research traffic
05Find out where you stand

SeeexactlyhowAIenginesaredescribingyourproducttoday.

Drop your domain. We'll run 200+ healthtech-specific queries across all six AI engines and send you a per-engine visibility score, an accuracy log of how your product is being described, and a competitor-citation gap analysis — within 48 hours.

No credit card. No sales call required to see the report.