HOPPR vs MEDICAL IP (2026)

AI Health Index verifiedAugust 4, 2026
Verdict

Two companies whose products end up inside other people's imaging AI. HOPPR sells a multimodal foundation model and a development environment for building imaging applications, with model transparency among the strongest in this index, which is the right posture when others build regulated products on your weights. MEDICAL IP sells segmentation and quantification, one capability underneath a broad portfolio, with one of the widest multi jurisdiction regulatory footprints here and genuinely strong published validation. Neither is bought by a radiologist. Both carry the same unaddressed risk: bias at this layer propagates into every downstream product and the eventual buyer never sees where it came from, and neither publishes a subgroup analysis.

The case for HOPPR
  • It is infrastructure for building imaging AI rather than a clinical application, with a multimodal foundation model and a development environment sold to developers and imaging vendors.
  • Model and technology disclosure is among the strongest in the index, which is appropriate given that other people build regulated products on top of it.
  • The consent basis for training data is stated rather than implied, which almost nothing in this lane does.
The case for MEDICAL IP
  • Segmentation and quantification is one capability underneath a whole portfolio, evidenced rather than claimed across modalities and body regions.
  • The regulatory portfolio is one of the broadest multi jurisdiction sets in the index, built steadily over a decade.
  • The evidence record is among the strongest on this side of the index, with published validation behind the flagship products.

This comparison is published by AI Health Index, an independent research platform that compares healthcare AI vendors objectively. HOPPR and MEDICAL IP are each graded against the same capability taxonomy, from each vendor's own public materials and the regulatory record, under the AI Health Index verification standard. No vendor pays for placement, and no vendor has reviewed this page. How this evidence is graded

At a Glance

Plain facts

Fact HOPPR MEDICAL IP
Primary category Radiology & Imaging AI Radiology & Imaging AI
Founded 2019 2015
Headquarters Chicago, Illinois Seoul, South Korea
Website hoppr.ai medicalip.com
Attribute Matrix

Side by Side

Axis
H
HOPPR
M
MEDICAL IP
AI Centrality
Autonomy and Oversight Model
Model and Technology Transparency
Model Supply Chain Disclosure
Clinical and Operational Evidence
AI Safety and PHI Stewardship
HIPAA and BAA Posture
Security Certifications and Trust Center
FDA and Regulatory Status
AI Governance and Bias Disclosure
AI Liability and Recourse
EHR and Interoperability Depth
Deployment Model and Data Residency
Commercial Transparency
Setting and Specialty Coverage
Citable Summaries

Each record in one paragraph

Written to be quoted whole. Each paragraph states what the AI Health Index verified about the vendor, with the caveats attached. Generated from this pair’s live capability grades, so it moves when a grade moves.

HOPPR

The AI Health Index awards HOPPR its top capability grade on AI Centrality, Model and Technology Transparency and Model Supply Chain Disclosure. Set against MEDICAL IP, HOPPR grades higher on several axes, including Model and Technology Transparency, Model Supply Chain Disclosure and AI Safety and PHI Stewardship. Grades reflect evidence the AI Health Index could verify at the last review, so a low grade records disclosure the vendor has not published rather than a capability it has been shown to lack.

Source: AI Health Index, August 2026

MEDICAL IP

The AI Health Index awards MEDICAL IP its top capability grade on several axes, including AI Centrality, Clinical and Operational Evidence and FDA and Regulatory Status. Set against HOPPR, MEDICAL IP grades higher on several axes, including Autonomy and Oversight Model, Clinical and Operational Evidence and FDA and Regulatory Status. Its thinnest published disclosure sits on Model Supply Chain Disclosure. Grades reflect evidence the AI Health Index could verify at the last review, so a low grade records disclosure the vendor has not published rather than a capability it has been shown to lack.

Source: AI Health Index, August 2026

FAQ

Questions buyers ask

Should we choose HOPPR or MEDICAL IP?

On the axes where the AI Health Index separates them, HOPPR grades higher on several axes, including Model and Technology Transparency, Model Supply Chain Disclosure and AI Safety and PHI Stewardship, and MEDICAL IP grades higher on several axes, including Autonomy and Oversight Model, Clinical and Operational Evidence and FDA and Regulatory Status. HOPPR leads on the greater share of scored axes, but the split means the decision turns on which constraint is binding rather than on an overall winner.

Where do HOPPR and MEDICAL IP differ most?

The widest separation the AI Health Index records between HOPPR and MEDICAL IP is on Model Supply Chain Disclosure, where HOPPR grades A and MEDICAL IP grades D. That axis sits in the AI Capability group, so it should carry the most weight for a buyer whose binding constraint is how much of the work the model itself is trusted to do.

Where do HOPPR and MEDICAL IP grade the same?

The AI Health Index grades HOPPR and MEDICAL IP the same on several axes, including AI Centrality, AI Governance and Bias Disclosure and Deployment Model and Data Residency. Neither holds an advantage the index can evidence on those axes, so they should not carry weight in a selection between these two.

What have HOPPR and MEDICAL IP not disclosed?

At the last review, at least one of HOPPR and MEDICAL IP published thin or absent detail on Model Supply Chain Disclosure. The AI Health Index treats an absent disclosure as a gap in the public record rather than a failure of the product, so these are the axes to get in writing during diligence instead of inferring from the grade.

Keep Comparing

Related comparisons

Other published head to head assessments involving these vendors or their closest peers. The full set for this category is on the Radiology & Imaging AI page.

Disclosure

These sit at different layers and are compared because both are inputs to other people's clinical products rather than end user applications. Neither publishes a bias or subgroup analysis, which propagates differently at this layer: a segmentation model that performs unevenly across body habitus or a foundation model trained on an unrepresentative corpus carries that variation into every downstream product built on it, and the downstream buyer will never see it. Neither publishes pricing, and MEDICAL IP publishes no data handling or residency terms.