Heartflow vs Viz.ai (2026)
Both change what happens after a scan rather than only what a radiologist sees in it, in different cardiovascular pathways. Heartflow analyses coronary computed tomography to quantify plaque and stenosis, and the outcome it moves is whether a patient goes to the catheterisation laboratory at all, which is measurable in cost and in avoided procedural risk. Viz.ai detects and then mobilises, holding the first ever authorization for computer aided triage and notification, with evidence measuring care delivery rather than model accuracy. A cardiology service and a stroke service would each buy one and not the other. What both illustrate is the same lesson: the imaging AI that pays for itself is the one wired into a decision, not the one that produces a better description of the image.
- The coronary computed tomography analysis is the product, quantifying plaque and stenosis in a way that changes the downstream care pathway rather than the reading order.
- The clinical evidence base in cardiac imaging is deep and the outcome being changed is invasive testing avoided, which is measurable in both cost and patient risk.
- For a cardiology service the question is which patients need the catheterisation laboratory, and that is what this answers.
- Its stroke product received the first ever authorization for computer aided triage and notification, and the platform's real work is mobilising the treating team.
- The evidence measures care delivery rather than detection accuracy, which is the harder result and the one that corresponds to patient benefit.
- For a time critical pathway the constraint is coordination rather than interpretation, and the communication layer is the product.
This comparison is published by AI Health Index, an independent research platform that compares healthcare AI vendors objectively. Heartflow and Viz.ai 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
Plain facts
| Fact | Heartflow | Viz.ai |
|---|---|---|
| Primary category | Radiology & Imaging AI | Radiology & Imaging AI |
| Founded | 2007 | 2016 |
| Headquarters | Mountain View, California, United States | San Francisco, California, United States |
| Website | heartflow.com | viz.ai |
Side by Side
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.
The AI Health Index awards Heartflow its top capability grade on several axes, including AI Centrality, Clinical and Operational Evidence and Security Certifications and Trust Center. Set against Viz.ai, Heartflow grades higher on several axes, including Model Supply Chain Disclosure, AI Safety and PHI Stewardship 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
The AI Health Index awards Viz.ai its top capability grade on several axes, including AI Centrality, Autonomy and Oversight Model and Clinical and Operational Evidence. Set against Heartflow, Viz.ai grades higher on Autonomy and Oversight Model and Setting and Specialty Coverage. 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
Questions buyers ask
Should we choose Heartflow or Viz.ai?
On the axes where the AI Health Index separates them, Heartflow grades higher on several axes, including Model Supply Chain Disclosure, AI Safety and PHI Stewardship and HIPAA and BAA Posture, and Viz.ai grades higher on Autonomy and Oversight Model and Setting and Specialty Coverage. Heartflow 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 Heartflow and Viz.ai differ most?
The widest separation the AI Health Index records between Heartflow and Viz.ai is on Model Supply Chain Disclosure, where Heartflow grades B and Viz.ai 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 Heartflow and Viz.ai grade the same?
The AI Health Index grades Heartflow and Viz.ai the same on several axes, including AI Centrality, Model and Technology Transparency and Clinical and Operational Evidence. 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 Heartflow and Viz.ai not disclosed?
At the last review, at least one of Heartflow and Viz.ai 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.
Related comparisons
Other published head to head assessments involving these vendors or their closest peers. The full set for this category is on the Clinical Decision Support page.
These sit in different cardiovascular workflows and are compared because both change what happens after the scan rather than only what is seen in it. Viz.ai publishes no independent security attestation and no business associate terms, and no hosting or residency terms were located. Neither publishes subgroup performance, which matters in cardiac imaging because plaque characterisation and stroke presentation both vary by sex and the evidence bases historically under represent women. Neither publishes pricing.