Talk to Dr. Galen — an AI emergency physician that listens, reasons, checks for diagnostic bias, and recommends the right level of care with actionable next steps.
Dr. Galen
Can you describe the tightness — is it sharp, dull, or pressure-like?
It's more like pressure on my chest...
Bias Alert: ACS
Bias Check
Active
Vitals
Phone Camera
An estimated $32B is spent each year on ER visits that could be handled in lower-cost settings.1 Median visit times have climbed to 2 hours 40 minutes and over 4 hours for patients who need admission.2
Life-threatening conditions are missed along predictable lines. Women are 50% more likely to be misdiagnosed after a heart attack.3 Young adults with stroke are misdiagnosed up to 14% of the time, often sent home with a migraine or vertigo diagnosis.4
Asclepiad closes the gap.
An AI that triages with clinical precision, catches the biases humans miss, and gives you clear next steps.
1 UnitedHealth Group, “The High Cost of Avoidable Hospital Emergency Department Visits,” 2019
2 CMS Timely and Effective Care data, 12-month average ending Q3 2022
3 Wu et al., European Heart Journal: Acute Cardiovascular Care, 2018; University of Leeds, MINAP registry (n = 564,412)
4 Kuruvilla et al., Journal of Stroke and Cerebrovascular Diseases, 2011; Newman-Toker et al., Diagnosis, 2014
$32B
In avoidable ER spending per year, according to UnitedHealth Group
UnitedHealth Group, 2019
50%
More likely for women to be misdiagnosed after a heart attack
Wu et al., EHJ: Acute Cardiovascular Care, 2018
~14%
Of young adults with stroke are misdiagnosed in the ER
Kuruvilla et al., J Stroke Cerebrovasc Dis, 2011
2h 40m
Median total ER visit time; 4.3h if admitted
CMS Timely & Effective Care, 2022
Three AI engines work together to give you an ER-quality assessment in minutes, not hours.
Describe your symptoms by voice or text. Dr. Galen asks the right follow-up questions, just like a real ER doc.
Claude builds a differential diagnosis, cross-checks against medical literature, and watches for diagnostic bias.
Perplexity searches real-time medical knowledge — guidelines, drug interactions, local resources — to verify every conclusion.
Get a clear recommendation with next steps: self-care plan, telemedicine handoff, or immediate ER direction with a pre-arrival packet.
Not every problem needs the ER. Not every patient should stay home. Asclepiad gets it right.
Personalized care plan with treatment steps, OTC medication guidance, warning signs to watch for, and clear follow-up instructions.
Structured clinical handoff for a physician: HPI, differential diagnosis, bias flags, and recommended workup, all in one document.
Immediate action steps, nearest ER with directions, pre-arrival clinical summary for the care team, and a 911 dispatcher script.
Every assessment is checked against peer-reviewed diagnostic bias patterns. When your demographics match a known under-diagnosis pattern, the system flags it, cites the evidence, and adjusts the recommendation upward.
Because the patients most likely to be sent home are often the ones who need help most.
Diagnostic Bias Alert
Acute Coronary Syndrome
Female, age 34
Women are 50% more likely to be initially misdiagnosed after MI
Wu et al., EHJ: Acute Cardiovascular Care, 2018
AI Adjustment
Escalate to Tier 3. Recommend cardiac workup even with atypical presentation.
Each engine specializes in what it does best. Together, they deliver ER-grade clinical reasoning.
GPT-5.2 acts as an empathetic ER physician: warm, thorough, asking the right questions one at a time. Voice or text.
Claude Opus 4.6 analyzes the conversation in real time: building a differential, checking for diagnostic bias, and deciding the right tier.
Perplexity Sonar provides real-time medical knowledge: guidelines, drug interactions, FDA alerts, and PubMed evidence when needed.
No downloads, no sign-ups. Just tell Dr. Galen what's going on, and get the right level of care in minutes.