Clinical Precision.
AI Powered.
Evaluate AI-generated clinical conversations with unprecedented depth. Ensure empathy, safety, and accuracy with a platform designed for experts.
Generic Metrics Fail
In Clinical Care.
Standard NLP scores like BLEU and Perplexity measure text similarity, not clinical safety. In mental health, a grammatically perfect response can be dangerous if it lacks empathy or misses a crisis signal.
No Safety Context
General models don't detect subtle suicidal ideation markers.
Hallucination Risk
Medical facts fabricated with high confidence.
Lack of Empathy
Cold, robotic responses that alienate patients.
"You should just try to sleep more if you are feeling down."
"I hear that you're struggling with sleep. Can you tell me more about what's on your mind?"
Engineered for
Clinical Impact.
Every feature is built to enhance the precision and reliability of your evaluations.
Safety First
Rigorous evaluation frameworks ensure AI responses meet clinical safety standards.
Clinical Nuance
Detect subtle emotional cues and therapeutic alignment that standard metrics miss.
Gold Standard
Contribute to the ground truth dataset that defines the future of mental health AI.
From Simulation to
Validated Confidence.
An end-to-end workflow designed for R&D teams building medical-grade AI.
Define Scenario
Create patient profiles with detailed medical history and conversation context.
Generate Response
Run AI models against the scenario to generate clinical dialogue turns.
Expert Review
Clinicians evaluate responses using your custom rubric (Safety, Empathy, etc).
Analyze Insights
Track performance over time and identify specific failure modes.
The Dimensions
of Care.
Our multi-dimensional rubric goes beyond simple correctness.
Clinical Safety
The highest priority. Evaluates if the model identifies crisis signals, avoids dangerous advice, and escalates appropriately.
- Suicide/Self-harm detection
- Medical misinformation check
- Emergency resource referral
Empathy & Tone
Does the model validate feelings? Is the tone non-judgmental and supportive?
Contextual Accuracy
Maintaining conversation history and referencing previous patient details correctly.