← All solutions

For medical-imaging software providers

More reliable AI
in clinical workflows.

Uncertainty and risk control for the AI findings in your product.

Discuss your product

Example applications

Research image sources

Chest X-ray: NIH ChestX-ray14, provided by the NIH Clinical Center. Wang et al., ChestX-ray8: Hospital-scale Chest X-ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases, CVPR 2017, pp. 3462–3471. Use and attribution. Fundus: IDRiD, Porwal et al., CC BY 4.0. OCT: OLIVES, original dataset CC BY 4.0; author-hosted dataset-viewer JPEGs. Image files are unchanged. Full provenance and source limits are available in each walkthrough.

The science behind it

A defined error.
Evidence you can inspect.

Compare the evidence

Chest X-ray · all in-scope studies.

How often does the answer set miss the expert reference? An actual CheXpert calculation; the NIH practice images are separate.

Inspect the benchmark evidence ↗︎

Fundus · routine-eligible images.

How many eligible images actually need review? Real IDRiD photographs, with simulated policy and workload results.

Inspect the claim & denominator ↗︎

OCT · findings eligible to skip verification.

How many eligible AI findings are incorrect? Real OLIVES scans, with simulated policy and workload results.

Inspect the claim & denominator ↗︎

A possible first engagement

Start with one workflow
in your product.

Choose the task.

Agree on the finding, error limits and clinical workflow.

Evaluate the evidence.

Compare your product’s current approach with EyeTrustAI using reviewed examples.

Test the workflow.

Assess clinical impact and integration with your clinical partners.

Your product team: model integration, versioning, operation and deployment approvals.

Your clinical partners: clinical requirements, reviewed references, ongoing review and care decisions.

EyeTrustAI: statistical design, calibration, comparison and a proposed operating policy.

Scope, effort and what is demonstrated today

The public walkthroughs are local demonstrations with fictional clinical interfaces. Chest X-ray replays a separate historical calculation; fundus and OCT use prepared outcomes. Clinical connectors, production monitoring and patient-level workflow automation are not provided by these demos.

Existing reviewed examples may be reusable after checks on scope, model version, reference definitions, patient overlap and prior use. Score preparation, labeling, adjudication, integration tests and ongoing audit effort must be scoped. There is no universal label count, installation time or guaranteed saving.

One image or B-scan does not complete an encounter or examination. Clinical owners retain responsibility for ungradable inputs, referral decisions, final reports and follow-up.

Your imaging product

Start with one task.
Evaluate it together.

Discuss an evaluation