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How much does OpenEvidence earn?

iOS app from OpenEvidence Inc. · Medical

ML forecast ★ 4.9 · 10K +39.9% MoM Freemium

~1.0K/mo

ML revenue forecast. Calibrated against 270 apps in this category.

Confidence band
±15%
High — many comparable apps with verified data

At a glance

OpenEvidence's revenue trajectory

Forecast revenue from snapshot history. Last 22 months.

Where OpenEvidence sits in Medical

Revenue distribution of 270 comparable apps. OpenEvidence highlighted.

OpenEvidence vs comparable apps

Revenue trajectory side-by-side. Bold = OpenEvidence, ghosted = peers.

App spec

Version
2.9.11
Last update
Jun 02, 2026
Launched
Aug 15, 2024
Min OS
15.1
Rating
17+
Price
Free
Monetization
Freemium
Languages
EN

What OpenEvidence actually does (from App Store listing)

Clinical Decision Support & Medical Search Engine for Healthcare Professionals (NPI Required). OpenEvidence is trusted by hundreds of thousands of verified healthcare professionals to support high-stakes clinical decisions at the point of care with answers that are sourced, cited, and grounded in peer-reviewed medical literature. OpenEvidence is the fastest-growing and most widely-used clinical decision support platform in the world–used daily, on average, by over 40% of physicians in the Uni…
Read full description →

🆕 What's new · v2.9.11

* NEJM, JAMA, and NCCN content partnership * Streamlined experience during answer writing * Performance enhancements

Comparable iOS apps

The five apps in Medical with the closest revenue to OpenEvidence. Click any to see its detail page.

AppRevenueRatingRatings
Ascension One icon Ascension One 1.0K ★ 4.8 9K
Alto Pharmacy icon Alto Pharmacy 1.0K ★ 4.8 7K
ScriptSave WellRx Rx Discounts icon ScriptSave WellRx Rx Discounts 1.0K ★ 4.8 8K
My Health at Vanderbilt icon My Health at Vanderbilt 1.0K ★ 4.7 8K
Count the Kicks! icon Count the Kicks! 1.0K ★ 4.8 9K
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How we calculated this

Each forecast combines App Store rating, ratings count, monetisation model, pricing tier, IAP signals and ad-supported flag. The base estimate is then multiplied by a per-category scaling factor learned from apps with founder-verified MRR. Every number on this page comes from public APIs and bumetric's own snapshot history.

Full methodology covers input variables, accuracy bands per category and how we treat apps without comparable anchors. See also the live data on OpenEvidence's tracker page for current rating, reviews and snapshot timeline.

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