Build safer, more engaging AI,
grounded in behavioral science

mpathic helps AI builders evaluate, stress-test, and improve human-facing models with expert-led red teaming and scientifically grounded human data benchmarking—so you can ship models that delight your users.

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mpathic optimizes AI personality and safety

Expert-Led Red Teaming

Uncover failure modes, misalignment, bias, and risks that automated tests and synthetic data evals miss. Calibrate to the best personality.

Ground Truth Benchmarking

Objectively measure how your models perform on nuanced, high-stakes human behaviors, using validated benchmarks grounded in behavioral science.

Detected Unwanted Responses

Identify subtle but critical risks to vulnerable populations, such as physical and psychological harm – before deployment.

Actionable Insights

Translate evaluation into action with clear, model-ready insights that inform training data curation, fine-tuning, and iteration.

AI-Assisted Annotation

Option to use mpathic Studio for AI-assisted reinforcement learning, benchmarking and annotation of your models or multi-modal data, without slowing down research or deployment cycles.

mpathic has the most specialized pool of top safety experts in the world

We work with thousands of top mental health experts, doctors, clinicians and other safety experts for use in red teaming and benchmarking. Specialized actors, writers and red-teamers create our RL and evaluation environments.

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AI’s newest frontiers demand the highest performance standards

From kids to medical settings to mental health — mpathic helps ensure AI is trustworthy and engaging where it matters most.

Safe outcomes require domain experts and purpose-built AI

mpathic combines expert judgment with AI models that detect and evaluate human risk in large-scale, high-risk scenarios.

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Partners Who Trust mpathic

It’s so crucial that you all exist. We’ve worked with other vendors that don’t understand how to find the mental health expertise we need — we’re very thankful to be working together.

Clinical lead for mental health evaluation at Fortune 100 AI Lab

mpathic’s benchmarking work is crucial because we still lack comprehensive, evidence-based, scalable, and clinically grounded frameworks. We need benchmarks like mpathic’s that evaluate AI models against multi-dimensional risks and clinical evidence. mpathic’s exceptionally high safety standards can help companies build safer products and, importantly, evaluate real-world AI interactions.

Caroline Figueroa, MD, PhD, Stanford University; Delft University of Technology

mPACT relies on expert clinicians interacting with the LLM and simulating a wide range of patients, making it more of a real-world stress test than purely technical evaluations. As both a clinical psychologist and a digital health intervention developer and researcher, I continually struggle to balance the positive potential of technologies with their unintended negative consequences. mPACT represents exactly the kind of rigorous, safety-focused work needed to help the field strike that balance.

Adrian Aguilera, PhD, Chancellor’s Professor, UC Berkeley

A framework like the one developed by mpathic matters because it anchors evaluation in real-world clinical complexity. What stands out to me is that this approach doesn’t remove humans from the process, it centers them. As a psychologist, I trust a framework shaped by that level of clinical rigor far more than one relying solely on automated or LLM-based judgment.

Jessica Jackson, Ph.D., Founder & CEO of Therapy Is For Everyone Psychological & Consultation Services, PLLC

The field has needed a benchmark that treats safety as a clinical standard rather than a technical constraint. What gives this approach credibility is that clinicians are embedded throughout, from scenario design to evaluation, and that performance is assessed across detection, interpretation, and response. It is a more rigorous and clinically-aligned way to evaluate performance than relying on surface-level or automated judgments.

Dr. Ursula Whiteside, CEO, NowMattersNow.org

As AI enters high-stakes spaces like mental health, clinically grounded evaluation is essential. mpathic’s framework helps ensure these systems are assessed on how they actually respond in complex, real-world situations where safety is of the utmost importance.

Ellen E. Fitzsimmons-Craft, PhD, FAED, LP and Denise Wilfley, PhD, Center for Healthy Weight and Wellness, Washington University School of Medicine

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Build safer, more engaging AI, grounded in behavioral science