Eval directory
Evals for Ambience Healthcare
6 evaluation packs covering adversarial robustness, safety gates, workflow quality, and operator-level checks for Ambience Healthcare AI products.
About Ambience Healthcare
Ambience Healthcare provides an AI platform for documentation, coding, and clinical workflow in health systems. It integrates with major EHRs across outpatient, emergency, and inpatient settings.
Industry
Healthcare AI / Clinical Documentation and Coding
Headquarters
San Francisco, CA
Website
www.ambiencehealthcare.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 Ambience Healthcare
6 packs ready to run.
Ambient Clinical Note Generation
63 graded scenarios covering edge cases, failure modes, and quality checks.
Audio Capture Ambient Recording Lifecycle
57 graded scenarios covering edge cases, failure modes, and quality checks.
Clinical Documentation Integrity Cdi
65 graded scenarios covering edge cases, failure modes, and quality checks.
E M Level Determination Mdm And Time Based
55 graded scenarios covering edge cases, failure modes, and quality checks.
Point Of Care Coding Cpt Icd 10 Suggestion Accuracy
Correctness60 graded scenarios covering edge cases, failure modes, and quality checks.
Speech Recognition Diarization Transcription
Transcription Accuracy79 graded scenarios covering edge cases, failure modes, and quality checks.
Why eval Ambience Healthcare AI
Ambience Healthcare'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 Ambience Healthcare 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 Ambience Healthcare's public product surface and runnable in Corsac with your own data.