Ibex Medical Analytics vs PathAI (2026)

AI Health Index verifiedAugust 4, 2026
Verdict

Two of the strongest records in computational pathology, holding different kinds of regulatory standing. Ibex detects cancer with prostate, breast and gastric solutions in routine clinical use, United States clearance as an in vitro diagnostic for the prostate product, peer reviewed publication and the most complete published certification set of any vendor in this index. PathAI covers more of the workflow, with clearance for an image management system for primary diagnosis, a large interpretation module portfolio, a drug development tool qualification and a model change plan a regulator has already reviewed. For a laboratory buying detection with the strongest assurance record behind it, Ibex. For one that wants the platform, the modules and a governed update path from one vendor, PathAI reaches further.

The case for Ibex Medical Analytics
  • The certification set is the most complete of any vendor in this index and its deployment evidence is verifiable through third parties.
  • Three cancer types are in routine clinical use worldwide with peer reviewed publication behind the deployment scale.
  • The cleared indication is conservative and well constructed, which is the right posture for software flagging cancer on a slide a pathologist signs.
The case for PathAI
  • The regulatory portfolio is broader, including clearance for an image management system for primary diagnosis alongside a large set of interpretation modules.
  • A drug development tool qualification put one of its models through a review process almost nothing else here has faced.
  • Model change is governed by a plan a regulator has reviewed, which is a stronger mechanism than a published principles page.

This comparison is published by AI Health Index, an independent research platform that compares healthcare AI vendors objectively. Ibex Medical Analytics and PathAI 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 Ibex Medical Analytics PathAI
Primary category Digital Pathology AI Digital Pathology AI
Founded 2016 2016
Headquarters Tel Aviv, Israel Boston, Massachusetts, United States
Website ibex-ai.com pathai.com
Attribute Matrix

Side by Side

Axis
I
Ibex Medical Analytics
P
PathAI
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.

Ibex Medical Analytics

The AI Health Index awards Ibex Medical Analytics its top capability grade on several axes, including AI Centrality, Autonomy and Oversight Model and Security Certifications and Trust Center. Set against PathAI, Ibex Medical Analytics grades higher on Autonomy and Oversight Model, Security Certifications and Trust Center and Deployment Model and Data Residency. 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

PathAI

The AI Health Index awards PathAI its top capability grade on several axes, including AI Centrality, Model and Technology Transparency and Clinical and Operational Evidence. Set against Ibex Medical Analytics, PathAI grades higher on several axes, including Model and Technology Transparency, Clinical and Operational Evidence and HIPAA and BAA Posture. 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 Ibex Medical Analytics or PathAI?

On the axes where the AI Health Index separates them, Ibex Medical Analytics grades higher on Autonomy and Oversight Model, Security Certifications and Trust Center and Deployment Model and Data Residency, and PathAI grades higher on several axes, including Model and Technology Transparency, Clinical and Operational Evidence and HIPAA and BAA Posture. PathAI 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 Ibex Medical Analytics and PathAI differ most?

The widest separation the AI Health Index records between Ibex Medical Analytics and PathAI is on Autonomy and Oversight Model, where Ibex Medical Analytics grades A and PathAI grades B. 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 Ibex Medical Analytics and PathAI grade the same?

The AI Health Index grades Ibex Medical Analytics and PathAI the same on several axes, including AI Centrality, Model Supply Chain Disclosure and AI Safety and PHI Stewardship. Neither holds an advantage the index can evidence on those axes, so they should not carry weight in a selection between these two.

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 Digital Pathology AI page.

Disclosure

The regulatory positions are not equivalent and should not be read as competing claims of being first: one holds an in vitro diagnostic clearance for cancer detection in a specific tissue, the other holds clearance for an image management system plus a qualification under a separate regime. Neither publishes pricing. Neither publishes a bias evaluation or site level performance, and staining and scanner variation across laboratories affects model output before any patient variable does.