For pharma brand and omnichannel teams

Know what AI tells patients and HCPs about your brand.

We run the treatment questions in your indication through ChatGPT, Gemini, Perplexity, and Grok. You see:

Whether your brand is named, vs. competitors
Which brand gets credit for your key messages
Which claims need review against your PI

Request a baseline See a sample report

MonitorsChatGPTGeminiPerplexityGrok

ExampleRx · AI Pulse 74▼4

Sample data

This cycle

Needs action

Named in broad answers. Missing when HCPs ask what to switch to.

All of the drop comes from one question group. Open those answers to see who is named instead.

Answers naming ExampleRx · Last two cycles

80%72.5%

384 → 348 of 480 answers · Same 40 questions

Where the drop is

“What should I use after first-line treatment?”

−36 mentions

See the full example

Why it matters

AI now answers the questions your brand used to own.

More than 40 million people ask ChatGPT health questions every day. Your search, social, and media reports don’t show what they’re told.

Source: Healthcare Dive, January 2026

Left out

An HCP asks about treatment options in your indication. Your brand isn't in the answer.

Out-positioned

A competitor gets credit for the benefit your campaign is built on.

Off label

The answer overstates your PI and cites a source your team has never reviewed.

The cost of waiting

It isn’t a crisis. It’s a blind spot.

Start with one brand. The baseline becomes the reference point for every later decision.

Gaps surface late.

You hear about them from the field or an MLR escalation, not a report.

Briefs run on guesswork.

Agencies plan content without knowing which questions and pages shape AI answers.

No baseline, no proof.

Without a starting point, you can't show what your content changed.

What you get

One score. Four measures. Every number traced to the answer.

AI Pulse score

One number for how AI represents your brand, tracked every cycle. Built from visibility, positioning, and PI alignment.

Share of Answer

% of answers that name your brand, vs. each competitor.

Positioning

First choice, alternative, or not mentioned.

Message credit

Which brand AI credits with each of your key benefits.

PI alignment

Claims that may conflict with your PI, flagged for Medical.

Product tour

Brand health at the top. The evidence one click down.

Start with what changed. Then open the questions behind it, the messages competitors own, and the pages AI cites.

Product tour · Sample data

Brand view

What changed this cycle?

ExampleRx · Brand overview

AI Pulse 74▼4

Losing the switching conversation.

Named in 348 of 480 answers, down from 384. Broad category visibility is flat.

Share of Answer · 6 → 20 Sep 2026

80% → 72.5%

40 questions × 4 platforms × 3 repeats. Fictional data.

By question group

Broad treatment options108 → 108 / 120

After first-line treatment108 → 72 / 120

Administration & dosing84 → 84 / 120

Long-term treatment84 → 84 / 120

Blue = current cycle. Two cycles show a change, not a trend.

Who it’s for

Same answers. Each team sees the decisions it owns.

Find where your brand is losing ground in AI answers.

Questions you can answer

Where are we missing, by question and platform?
Which of our messages do competitors own?
Which pages do we fix first?

Example findingSample data

Finding

ExampleRx is named in 90% of broad treatment answers, but only 60% when HCPs ask what to use after first-line therapy.

So what

The brand is losing the switching conversation. The overall score hides it.

Next steps

Pull the 48 switching answers that omit ExampleRx and list the pages they cite.
Check whether your HCP site answers the switching question directly.
Brief the agency on an MLR-approved switching page.
Re-run the same questions next cycle.

Case studies

Three teams. Three decisions changed.

All case studies

Pre-launch · Specialty launch

A launch team rewrote its brief before it spent on the campaign.

Found: The audience needed the problem explained before the mechanism could land.
Result: A new message hierarchy and two education briefs, before creative was locked.

Read the case study In-market · Established brand

An in-market brand sharpened its media plan around the websites AI cites.

Found: The agency needed to know which gaps were worth funding, and which sites to skip.
Result: A website investment plan: one row per site, with the question, evidence, action, owner, and next decision.

Read the case study Label update · New indication

After a new indication was approved, AI kept describing the old label.

Found: AI answers were running on the old label. The fix started with the pages AI already cites.
Result: A clear view of where AI still described the old label, by platform and question.

Read the case study

How it works

Set up once. A readout every cycle.

1
Scope
Agree the indication, competitors, key messages, and patient and HCP questions.
2
Run
The same questions go to ChatGPT, Gemini, Perplexity, and Grok every cycle, with repeat runs.
3
Read out
See what changed, which questions drove it, which sources AI cited, and who should act.
4
Re-run
After approved content goes live, run the same questions to see what moved.

Built for regulated teams. No black-box scores.

Read the methodology

Full answer text

Saved and timestamped, exactly as the AI wrote it.

Every cited source

The pages the AI linked to in each answer.

PI comparison

Possible conflicts with your label, flagged for human review.

No patient data

We analyze AI answers. We never need PHI.

Get started

See your brand’s baseline.

Tell us the brand and indication. We build the question set, run it across four AI platforms, and walk your team through the results.

Your indication, competitors, and key messages
AI Pulse score, Share of Answer, message credit, and PI flags
A readout for Brand, Omnichannel, and Medical

Not ready to talk? See a sample report