EyeTrustAIEyeTrustAI solutions
Start with the uncertainty
in your workflow.
Explore how a defined error, relevant reference data, and calibrated statistical control can come together in the tools your team already uses.
Domain demonstrations · Pilot enquiries welcome
Clinical documentation
More reliable clinical notes.
Less unnecessary checking.
Control the risk of errors in your scribe’s notes, within the limits you set.
Illustrative example · Reported allergy history
The patient says “Penicillin gave me a rash.”
The draft says “No known drug allergies.”
Target additional source checks. Retain final clinician review.
Invoice processing
Less manual invoice checking.
Controlled error risk.
Control extraction error risk in your product, within the limits you set.
For invoice-automation providers
Risk control for your invoice product.
Works with your extraction pipeline. Matching, approval and payment controls stay in place.
Follow the complete journey, from reviewed examples to ongoing operation, using synthetic invoices and prepared outcomes.
Medical imaging
More reliable AI
in clinical workflows.
Uncertainty and risk control for the AI findings in your product.
Explore medical imagingCustomer support
More reliable AI replies.
Less unnecessary review.
Control error risk in your AI support product, within the limits you set.
Illustrative example · Refund communication
The order says awaiting approval.
The AI says “Your refund has been approved.”
Control incorrect promises and reduce routine reply checking.
One statistical foundation
A focused application.
A shared approach.
The demonstrations make the workflow concrete. A real deployment requires relevant evidence, a suitable method, and validation for its specific scope.
- Define the target
- Agree on the error, reference, population, and permitted interpretation.
- Establish the evidence
- Assess data quality, label availability, sampling, and model compatibility.
- Evaluate usefulness
- Measure the achievable trade-off before making an operational commitment.
Social intelligence
Less manual triage for your customers.
Controlled risk of missed priority mentions.
Add evidence-backed risk control to the AI behind your listening product. Establish how much customer review can be automated within agreed error limits.