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 AI is an AI company focused on clinical and healthcare applications, building tools that help medical teams triage patients, match clinical trials, and navigate complex care pathways more safely.
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.