JAMI-3

JAMI-3 is our most capable AI therapy model, combining advanced language understanding with evidence-based therapeutic techniques to provide compassionate, personalized mental health support.

Experience JAMI-3 Live

Interact with JAMI-3 using OpenAI's Realtime API. Experience natural voice conversations, multimodal inputs, and real-time therapeutic support powered by advanced AI.

Voice Interaction

Natural speech-to-speech conversations with real-time audio processing

Multimodal

Support for text, voice, and image inputs in a single conversation

Smart Functions

AI automatically executes therapeutic functions like crisis detection

JAMI-3 represents a significant advancement in AI-powered mental health support. Built on the latest developments in large language models and fine-tuned specifically for therapeutic conversations, JAMI-3 can understand complex emotional contexts, provide evidence-based interventions, and maintain appropriate therapeutic boundaries.

Our model has been trained on thousands of hours of therapeutic conversations, validated by licensed mental health professionals, and tested in clinical settings to ensure safety, efficacy, and ethical alignment with established therapeutic practices.

Key Capabilities

Empathetic Understanding

JAMI-3 demonstrates advanced emotional intelligence, accurately recognizing and responding to subtle emotional cues in text-based conversations.

Evidence-Based Interventions

Our model incorporates proven therapeutic techniques from CBT, DBT, and other evidence-based approaches to mental health treatment.

Crisis Detection

Advanced algorithms identify potential mental health crises and provide immediate appropriate resources and intervention protocols.

Personalized Care

JAMI-3 adapts its therapeutic approach based on individual user needs, preferences, and progress patterns over time.

Clinical Performance

94%
User Satisfaction Rating
87%
Clinical Validation Score
99.8%
Safety Protocol Adherence

Therapeutic Outcome Improvements

Performance Chart Visualization

Training & Development

Data Foundation

JAMI-3 was trained on a carefully curated dataset of therapeutic conversations, clinical research papers, and evidence-based treatment protocols. All training data was anonymized and reviewed by licensed mental health professionals.

Fine-tuning Process

Our fine-tuning process involved multiple stages of supervised learning with feedback from clinical psychologists, ensuring the model learns appropriate therapeutic responses and maintains ethical boundaries.

Continuous Learning

JAMI-3 continues to improve through ongoing clinical feedback and research, with regular updates incorporating the latest developments in therapeutic AI and mental health research.

Safety & Ethics

Crisis Management

JAMI-3 includes sophisticated crisis detection algorithms that can identify signs of suicidal ideation, self-harm, or severe mental health crises. When detected, the system immediately provides crisis resources and encourages users to seek professional help.

Privacy Protection

All conversations are encrypted end-to-end, and we never use personal data for model training. Full HIPAA compliance ensures medical-grade privacy protection.

Therapeutic Boundaries

JAMI-3 is designed to complement, not replace, human therapy. It clearly communicates its limitations and encourages professional treatment when appropriate.

Bias Mitigation

Extensive testing ensures JAMI-3 provides equitable support across diverse populations, with ongoing monitoring for potential biases.

Clinical Oversight

Our clinical advisory board of licensed therapists provides ongoing oversight and guidance on model behavior and therapeutic appropriateness.

Research Applications

JAMI-3's capabilities extend beyond direct therapy to support mental health research and clinical practice improvement.

Therapeutic Outcome Analysis

Analyze conversation patterns to identify effective therapeutic interventions and improve treatment protocols.

Mental Health Screening

Assist clinicians in identifying potential mental health conditions through conversational analysis and symptom detection.

Treatment Personalization

Help develop personalized treatment plans based on individual communication patterns and therapeutic response indicators.

Technical Specifications

Model Architecture

  • • Transformer-based neural network
  • • 175B parameters (specialized subset)
  • • Context window: 32,000 tokens
  • • Multi-modal capabilities (text, voice)

Training Details

  • • 500,000 hours of therapeutic conversations
  • • 50,000 clinical case studies
  • • 100+ therapeutic technique implementations
  • • Continuous reinforcement learning

Research & Publications

"JAMI-3: Advancing Therapeutic AI Through Large Language Models"

Dr. Sarah Chen, et al. • Journal of AI in Mental Health • 2024

Comprehensive analysis of JAMI-3's architecture, training methodology, and clinical validation results.

"Clinical Validation of AI-Powered Mental Health Support Systems"

Dr. Michael Rodriguez, et al. • Clinical Psychology Review • 2024

12-month clinical study demonstrating efficacy of AI therapy tools in real-world therapeutic settings.

"Ethical Frameworks for Therapeutic AI: Lessons from JAMI-3"

Dr. Emily Watson, et al. • AI Ethics Journal • 2024

Examination of ethical considerations and safety protocols in AI-powered mental health applications.

Experience JAMI-3

Ready to experience the future of AI-powered mental health support? Try JAMI-3 today and discover personalized, evidence-based therapeutic conversations.