Know where AI is safe to scale.

We measure disagreement between AI drafts and final radiologist reads case by case and over time so you can trust what holds up in practice.

Compare, score, and decide what you can trust and what you can scale.

A continuous loop between AI draft and the final radiologist read — field-level, every case, every modality.

Compare.

See exactly where AI diverges from the final read.
Field-level comparison of AI drafts versus radiologist reports across every case.

CASE · CT-04821 · DIFF 07 FIELDS
AI DRAFT
FINAL READ

Score.

Track trust over time.
Measure disagreement, edit friction, and drift across models, modalities, and radiologists.

AGREEMENT · ROLLING 96.4%

Decide.

Know what you can safely delegate.
Identify where AI holds up, where it needs supervision, and where it breaks.

Scale Review Fail

For teams deploying AI in radiology.

01
Teleradiology Groups
Scale reads without losing control of quality.
02
Private Radiology Practices
Adopt AI without guessing where it is safe.
03
Health Systems
Evaluate real world performance, not vendor claims.
04
Imaging Platforms and OEMs
Prove your AI holds up in clinical workflow.

We do not evaluate models. We monitor how they behave in your practice.

Run a real world validation in weeks.

We analyze your AI draft versus final reports with no workflow changes and minimal setup. You get a clear view of where performance holds up and where it breaks.

No workflow changes Uses your existing reports First insights within weeks
Response within 1 business day
Available this week
Direct
Dr. Ty Vachon

Dr. Ty Vachon

CEO, Veriloop
Practicing radiologist · 20+ yrs clinical

Talk to a radiologist at Veriloop. Ask the hard questions. Where agreement breaks, how drift shows up, and what actually counts as a miss.