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OpenEvidence raises $150M, valued at $5B, as open-source platform expands globally

1 reports1 sources10/21/2026 updated

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AI overview

OpenEvidence secured $150 million in Series C funding, achieving a $5 billion valuation and open-sourcing its platform to expand into 100 low- and middle-income countries. While a Mayo Clinic study demonstrated accurate evidence recommendations, the platform's clinical efficacy remains disputed; it underperformed in benchmark tests, and NYU Langone neurosurgeon Eric Oermann criticized the lack of performance studies and clinical implementation guidelines for individual AI tools.

Written with AI from the reporting · updated 10/21/2026

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  1. 1Unclassified fact stationOct 21, 00:00recorded Oct 21, 23:57single sourcerevised

    OpenEvidence获评临床效果有限

    Read original source ↗ Ars Technica · AIReplay this moment in the explorer
    Evidence & revisions · 1 source records
    Subject:
    OpenEvidence
    Action:
    评估临床效果
    Object:
    AI工具在患者案例研究中的表现
    Occurred (fact side):
    Oct 21, 00:00
    Ars Technica · AI ↗Report pageRevision 2 · currently revised
    Published (valid side):
    Oct 21, 23:14
    First seen (known side):
    Oct 21, 23:57
    Fact stationSingle source · one-sided claimRevised

    Copy may have been revised later; time replay is bounded. Layer labels group reading only, not causation between layers.

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Oct 21
  1. Ars Technica · AIRelated fact: single sourceSource report revised
    Ad-powered AI startup OpenEvidence expands global reach and faces mixed clinical validation

    Report first recorded Oct 21, 23:57

    OpenEvidence, a $15 billion ad-powered AI startup, has expanded its reach to 100 low- and middle-income countries, supported by Anthropic's Claude Science platform for literature mining. While a Mayo Clinic study found it provided accurate, evidence-based recommendations in sampled patient cases, other research, including a June paper in Nature, showed it underperformed general-purpose AI models like Google’s Gemini and OpenAI’s GPT on clinical benchmarks. Eric Oermann, a neurosurgeon at NYU Langone, noted a lack of research on individual AI tool performance and guidance for clinical implementation.

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