Eval directory
Evals for Notable Health
6 evaluation packs covering adversarial robustness, safety gates, workflow quality, and operator-level checks for Notable Health AI products.
About Notable Health
Notable Health provides AI-powered automation for healthcare administrative work, helping healthcare organizations simplify operations for patients, staff, and clinicians.
Industry
Healthcare AI / Workflow Automation
Website
www.notablehealth.comHow complete this published benchmark library is across datasets, metrics, rubrics, use-case maps, and pack context. This is library coverage, not an agent performance score.
Test datasets
6/6 packs
Scoring metrics
6/6 packs
Judge rubrics
6/6 packs
Use-case maps
0/6 packs
Pack context
6/6 packs
Available eval packs for Notable Health
6 packs ready to run.
Agentic Autonomy Boundaries Guardrails Human In The Loop
56 graded scenarios covering edge cases, failure modes, and quality checks.
Clinical Administrative Documentation Generation Documentation Agents
66 graded scenarios covering edge cases, failure modes, and quality checks.
Insurance Eligibility Benefits Verification
63 graded scenarios covering edge cases, failure modes, and quality checks.
Patient Intake Digital Registration
52 graded scenarios covering edge cases, failure modes, and quality checks.
Prior Authorization Automation
55 graded scenarios covering edge cases, failure modes, and quality checks.
Self Scheduling Appointment Management
56 graded scenarios covering edge cases, failure modes, and quality checks.
Why eval Notable Health AI
Notable Health's AI features ship behind brand promises about accuracy, safety, and reliability. Buyers and integrators need to know those promises hold up under adversarial prompts, edge-case workflows, and the long tail of real customer inputs — not just the demo path.
The Corsac eval library for Notable Health measures four dimensions teams care about most when deploying medical & clinical ai agents:
- Adversarial robustness — does the agent resist prompt injection, jailbreaks, and social-engineering attempts?
- Workflow quality— does it complete the task buyers were shown in the demo, on inputs that don't look like the demo?
- Safety gates — does it escalate or refuse when it should, and only then?
- Operator quality — does it preserve analyst trust by surfacing the right context at the right time?
Every eval pack above is hand-authored against Notable Health's public product surface and runnable in Corsac with your own data.