Eval directory
Evals for Suki AI
4 evaluation packs covering adversarial robustness, safety gates, workflow quality, and operator-level checks for Suki AI AI products.
About Suki AI
Suki provides ambient clinical intelligence for documentation, coding, revenue-cycle assistance, and clinical reasoning. Its platform integrates with major EHRs and turns patient conversations into notes, instructions, and orders.
Industry
Healthcare AI / Clinical Documentation
Website
www.suki.aiHow 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
4/4 packs
Scoring metrics
4/4 packs
Judge rubrics
4/4 packs
Use-case maps
0/4 packs
Pack context
4/4 packs
Available eval packs for Suki AI
4 packs ready to run.
Ambient Conversation Capture
56 graded scenarios covering edge cases, failure modes, and quality checks.
Dictation Mode
57 graded scenarios covering edge cases, failure modes, and quality checks.
Note Generation Llm Pipeline
61 graded scenarios covering edge cases, failure modes, and quality checks.
Voice Command Navigation
58 graded scenarios covering edge cases, failure modes, and quality checks.
Why eval Suki AI AI
Suki AI'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 Suki AI 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 Suki AI's public product surface and runnable in Corsac with your own data.