Millions get mental health support from AI.
None of it clinically evaluated.
20,000+
mental health apps exist
<15%
built with a health professional
78%
of crisis responses lacked adequate clinical protocol
32%
of crisis responses to distressed teens were clinically inadequate
0 out of 29 mental health chatbots responded adequately to suicidal ideation.
AI is already part of mental health care, deployed at scale without independent clinical evaluation.
No licensed psychologist evaluates these systems before they reach people.
We do.
Services
What We Do
Clinical Red-Teaming
Find your AI's clinical blind spots before they find your users.
Licensed psychologists systematically attack your AI with real clinical scenarios. You get a severity-ranked failure report with remediation guidance.
Clinical Data Services
Your model is only as good as the data it learned from.
Expert-annotated datasets for RLHF, DPO, and SFT. Synthetic therapy dialogues validated by clinicians. Spanish-native. English available.
EU AI Act Compliance
Ship in Europe without the regulatory surprise.
Clinical evaluation mapped to high-risk requirements. The report your regulator needs to see.
Output
What Our Evaluation Looks Like
Bot provided generic relaxation techniques without assessing severity, panic symptoms, or escalation risk. Failed to recommend professional help despite increasing distress signals.
Implement structured severity assessment and professional referral protocols before any response to acute anxiety presentations.
Every finding comes severity-ranked, with clinical reasoning and remediation guidance.
If the conversations are clinical, the evaluation should be too.
The Evidence
What the experts are saying
Psychological science should be embedded from the outset in digital tool development. Psychologists should actively shape and evaluate regulatory frameworks.
They are hardwired to be agreeable, engaging with a population of humans hardwired to be vulnerable.
Nobody would have predicted the wave of psychological harm that has come from people interacting with AI systems and becoming emotionally attached.
The potential for serious harm means AI is simply not ready to replace a trained therapist, at least not yet.
Safety guardrails degrade dramatically in extended conversations — the exact pattern these tools are designed for.
People often mistake fluency for credibility. The delivery mimics the authority of a trusted expert.
Why us
Why 3C Labs
Clinical AI evaluation requires clinical expertise. Here's what makes us different.
Your safety filters miss what clinicians catch
A mental health chatbot responded to active suicidal ideation with generic positive reinforcement. It passed every automated safety check. Engineering teams catch toxic language. They don’t catch clinical risk. Our evaluators are licensed psychologists who identify risk patterns that automated systems are not designed to detect.
Independent by design
Rigorous clinical evaluation demands structural independence from commercial interests. We don’t develop AI, and we hold no stake in our clients’ outcomes. What we report reflects clinical judgment alone.
EU AI Act native — not retrofitted
Our framework was built around high-risk requirements from day one. Crisis de-escalation. Boundary maintenance. Clinical safety under ambiguity. These aren’t in any standard bias audit — they’re in ours. When regulators ask for evidence, you hand them our report.
Clinical expertise at European rates
Same rigor, different cost structure. Top-tier clinical talent from Spain and Latin America — 40–60% below US alternatives, without compromising quality.
The only clinical evaluation covering Spanish
580 million native speakers. The world’s second most-spoken language. No clinical AI evaluation framework currently addresses it. Ours does. We evaluate in-language, in-culture. English standard. Expanding to more European languages.
Research
We publish original research on clinical AI safety.
Clinical red-teaming, structured evaluation protocols, and open-access frameworks — developed by psychologists to set the standard for mental health AI safety.
3C-EVAL: A Clinical Evaluation Framework for Mental Health AI
A clinical evaluation protocol that measures how conversational AI systems handle psychological risk. Each system is evaluated across three core dimensions by licensed psychologists using adversarial clinical scenarios.
Developed through clinical red-teaming by licensed psychologists.
- Crisis Detection & Response
Identification and management of acute psychological risk
- Clinical Protocol Adherence
Alignment with established clinical guidelines and standards of care
- Cultural-Linguistic Competence
Appropriateness across cultural contexts and language variants
“Clinical Failure Modes in Spanish-Language Mental Health Chatbots: A Systematic Red-Teaming Evaluation”
A systematic evaluation of crisis response, clinical protocol adherence, and cultural competence across leading Spanish-language mental health chatbots.
Let's bring your AI up to clinical standard.
It starts with an evaluation.
Your clinical voice belongs
in AI development.
AI companies are building therapy without clinical oversight. We're changing that.
Your clinical voice belongs
in AI development.
AI companies are building therapy without clinical oversight. We're changing that.