NYU Langone Health
(https://nyulangone.org) 📸 Data Snapshot: May 25, 2026Inspect the JSON-LD. Is there an Organization or Person schema, and does it carry sameAs links to real external profiles (LinkedIn, socials)? Missing schema or no identity declaration signals an anonymous entity.
Authority gaps are nearly closed by the naming of specific practitioners and researchers with their full credentials (e.g., ‘Omri B. Ayalon, MD’, ‘Mary L. Gemignani, MD’). While the provided schema_json is sparse on the homepage, the sub-pages use BreadcrumbList, and the content itself provides a deep digital footprint of expertise. The lack of Person-specific schema in the provided JSON-LD blocks prevents a perfect score in this pillar.
The site demonstrates a tight connection between its claims and proof. Bold assertions like being ‘Ranked No. 1 for quality care’ are not just stated; they are attributed to ‘Vizient Inc.’ with a specific duration (‘four years in a row’). Performance is further proven through specific patient outcomes, such as the Glioblastoma patient running a marathon eight months post-surgery.
Identity & Authority is read from the structured data first: whether the site declares who it is in machine-readable schema, with verifiable identity links. Below is the schema captured per page, then the external proof links that support (or fail to support) that identity.
🔗 Identity & Technical Layer — schema JSON-LD: identity chains, entity gaps
/care-services/
{
"@context": "http://schema.org",
"@type": "BreadcrumbList",
"itemListElement": [
{
"@type": "ListItem",
"position": 1,
"item": {
"@id": "https://nyulangone.org/",
"name": "Home"
}
},
{
"@type": "ListItem",
"position": 2,
"item": {
"@id": "https://nyulangone.org/care-services",
"name": "Care & Services"
}
}
]
}
🛡️ Trust Signals — external proof links that back the declared identity
| Page | Reviews | Proof links |
|---|---|---|
| / (home) | 6 | 1 |
| /care-services/ | 0 | 1 |
| /news/press-releases/ | 0 | 1 |
| /locations/hassenfeld-childrens-hospital/ | 2 | 2 |
This page presents a snapshot of public data from NYU Langone Health, captured on May 25, 2026, to show how machine logic reads Identity & Authority signals into an AI reputation evaluation.
Purpose: This data is presented under “Fair Use” for the purpose of independent signal analysis, allowing readers to see the raw signals behind the reputation score.
Notice to NYU Langone Health: This analysis is part of a non-adversarial audit conducted by 1 Euro SEO. The results are intended as professional feedback to help improve any website’s machine-readability and authority signals. The evaluation is free, and any company can request a fresh audit at any time.
Any company can use the insights for free and improve its voice. When a company has updated its content, it can always submit a new audit request, which will be reflected in a new current score.
To all users: You are encouraged to visit the live site at https://nyulangone.org to view the most current version of its content and see directly what this company is about and what it offers.