8.1 Overall
VERA HEALTH

Vera Health

Recommend Scored Nov 2026

Vera Health is a free AI clinical search tool for licensed clinicians and trainees that answers questions from more than 60 million papers, guidelines, consensus statements, and drug labels, links each claim to its source, and color-codes the strength of the evidence.

verahealth.ai

Strong fit

  • Clinicians who want sourced answers during patient care
  • Doctors outside the U.S. who want local guidelines alongside global research
  • Emergency physicians who use American College of Emergency Physicians (ACEP) clinical policies

Weak fit

  • Health systems that need an enterprise contract and EHR integration
  • Patients, since it is built for licensed clinicians
  • Anyone who wants an answer without checking the cited evidence
Vera Health homepage

Bottom line

Vera Health is a free, evidence-graded clinical search tool that more than 800,000 clinicians have taken up in a year, mostly by word of mouth. It suits clinicians who want every claim tied to its source and a clear signal when evidence is thin. It has 12 employees, and its studies inside academic medical centers are still under way.

Score breakdown

7.6
Clinician adoption and time saved
8.0
Clinical search and research product
8.8
Getting clinicians started
8.6
Knowing what you will pay

Weights: Outcomes 35% · Product 30% · Implementation 20% · Pricing clarity 15%.

Vera Health is used by doctors, nurses, and trainees who need a quick, sourced answer during patient care. It searches more than 60 million peer-reviewed publications, clinical guidelines, consensus statements, and drug labels, finds the evidence first, and then writes an answer in which each claim links to its research and is color-coded by strength of evidence, according to its funding announcement. When the evidence is thin, such as a single case report, Vera shows it in red.

Vera is free for licensed clinicians and medical trainees, and the company says it will stay free. It works with ACEP to include ACEP clinical policies with source attribution.

The closest competitors are OpenEvidence, Glass Health, and Doximity.

Maxime Allouch and Taieb Bennani co-founded Vera Health. On October 27, 2026 it announced a $28.5 million Series A led by Threshold Ventures, with Mantis VC and SV Angel, and with Y Combinator and Gradient investing again, bringing total funding to $32 million. Vera says it went from a few thousand clinicians a year ago to more than 800,000 in 190 countries, including about one in four physicians in Spain and Italy and one in seven in France, and that it has been the most downloaded clinical app worldwide every month since June, citing Appark download data.

Vera's chief scientific advisor, Dr. Bernard P. Chang of Columbia University, said the company is now testing whether the tool improves clinical reasoning inside academic medical centers. Those results are not out yet.

What clinicians say

"Level of evidence is the foundation of every guideline we write, and Vera Health is built on it." Scott M. Silvers, MD, Chair of the ACEP Clinical Policies Committee, in Vera's announcement.

"Vera Health surfaced evidence that raised my concern for pulmonary embolism, a potentially life-threatening blood clot in the lungs, and led me to broaden my evaluation." Dr. Bernard P. Chang, Vera Health chief scientific advisor, in Vera's announcement.

Competitor landscape

VendorOverallEase of implementation
OpenEvidence8.48.8
Vera Health8.18.8
Doximity6.97.1
Glass Health6.86.9

Pricing

ItemDetail
ModelFree for licensed clinicians and medical trainees.
What usually drives costNothing for individual clinicians.
What to ask before you buyHealth systems should ask Vera about enterprise terms and EHR access, which it has not published.
Published pricingFree for clinicians.

Leadership

  • Maxime AllouchCo-founder
  • Taieb BennaniCo-founder
Methodology
WeightFactorWhat it measures
35%Customer outcomesWhether buyers get measurable operational or clinical-workflow results after go-live
30%ProductCapability depth, reliability, and fit for the job the category buys
20%ImplementationHow hard it is to stand up, integrate, train, and stabilize
15%Pricing clarityWhether a buyer can model total cost without a mystery quote
LabelMeaning
Highly recommendStrong outcomes and product with manageable caveats
RecommendSolid fit for the right buyer; know the tradeoffs
ConditionalOnly with a specific use case or heavy caveats
Not recommendedAvoid for most buyers in this category

Read our full methodology for how we weight scores and assign recommend labels.