AYA Solution and Product Overview
Agentic AI for Mental Health for Africa
Intelligent screening, triage, clinical reporting, and longitudinal monitoring—powered by voice analysis and constrained generative AI, built for low-resource and post-conflict settings.
AYA is building scalable mental health infrastructure that listens, understands, and acts—one voice at a time.
The Problem
Tens of Millions Silent, Invisible, Suffering Across Africa. An invisible crisis unfolds. Over 150 million people are undiagnosed and untreated, struggling with depression, anxiety, and trauma, and are unsupported. They suffer in silence because the systems designed to help them simply don't reach them.
150+ million Africans with undiagnosed mental health conditions
Less than 5% detection rate in primary care—most people never get screened
12x shortage of mental health workers compared to WHO standards
Frontline workers are overwhelmed without tools, training, or supervision to help.
What AI-Powered Infrastructure Can Do
Reach people where they are — not where healthcare happens to exist
Support and extend the work of existing frontline workers, amplifying their impact
Operate reliably in resource-constrained, disconnected, and post-conflict settings
Provide scalable screening and triage to prioritize urgent cases and allocate limited resources efficiently
Deliver culturally adapted, language-sensitive conversational tools for early engagement and psychoeducation
Enable remote monitoring and follow-up through low-bandwidth channels (SMS, voice, offline apps)
Offer decision-support for frontline workers, combining AI insights with human judgment to reduce burnout and improve outcomes
Integrate with local care pathways and community networks to ensure continuity, privacy, and ethical use
Generate anonymized population-level analytics to inform public health planning and targeted interventions
Support capacity building by training and upskilling community health workers with AI-driven guidance and supervision
Real Stories. Real Impact. Real Change
In communities across Ethiopia and Uganda, AYA is transforming lives. These aren't just pilot programs—they're journeys of hope where people finally get the care they deserve.
Ethiopia
Lenegewa Women's Rehabilitation and Job Training Center
Empowering women survivors of trauma with AI-powered screening, connecting those with sex work, homelessness, and severe poverty experiences to healing support
Ethiopia
EECMY-DASSC
Bringing mental health screening to post-conflict communities, reaching people who've experienced violence and displacement with compassionate AI-powered care
Uganda
Karis Medical Center
Integrating voice AI into clinical care, continuously monitoring patient progress and outcomes to ensure support doesn't end at diagnosis
Voice AI to Clinical Action
Voice AI to Clinical Action: The Complete Care Pathway
AYA transforms voice into clinical intelligence. Frontline health workers use voice-based screening to capture psychological states, while constrained generative AI generates actionable clinical insights—empowering nurses, counselors, and clinicians to deliver care that reaches those who've been invisible.
Voice AI Screening: Hearing the Unheard
The foundation of care is listening. Our voice AI, trained on the Multilingual Multimodal Clinical Dataset from diverse populations across Africa, converts a 30-second voice sample into comprehensive psychological metrics—detecting indicators of depression, anxiety, and trauma that clinical staff might miss. This objective voice assessment becomes the input for constrained generative AI clinical reasoning.
60% detection rate vs. 5% current rate in primary care
Constrained GenAI: From Data to Clinical Reasoning
Voice metrics alone tell part of the story. Our constrained generative AI layer takes voice-derived psychological data and applies structured clinical reasoning—transforming numbers into actionable decisions. The system generates risk assessments, triage recommendations, and treatment pathway guidance, always constrained to evidence-based clinical protocols. 85-90% accuracy in clinical decision support, grounded in psychiatric standards and frontline worker feedback.
AI that thinks like a clinician—bounded by safety and evidence
Longitudinal Voice AI Monitoring: Sustained Healing
Recovery is a trajectory, not a moment. Repeated voice-based check-ins track psychological status over weeks and months, while constrained generative AI identifies patterns of improvement, flags deterioration, and alerts clinicians to opportunities for intervention. The system creates a living clinical record—objective voice data over time, combined with AI-guided interpretation, ensuring patients receive continuous support and supervisors gain visibility into population mental health trends.
Care that follows patients home—and keeps them connected
A Patient's Journey to Care
From a 30-second voice sample to a personalized clinical plan. Meet Amara, a woman in Ethiopia, and follow her journey through AYA's intelligent screening, analysis, and care system.
30-Voice Sample: Sharing Her Story
Amara visits her local health clinic. A community health worker conducts a voice-based screening in Amharic, asking open-ended questions about her emotional state and well-being. Over one minute, she shares her experience—sadness about recent loss, anxiety about her family's future, and difficulty sleeping.
The 30-second voice sample captures genuine emotional expression—the foundation for AI analysis.
Voice AI Analysis: Objective Psychological Metrics
AYA's voice AI, trained on the Multilingual Multimodal Clinical Dataset, analyzes Amara's voice in real-time. The system calculates a comprehensive psychiatric severity score: Emotional Distress Index (EDI) and clinical formulation
Constrained GenAI Clinical Report: Structured Clinical Reasoning
Amara's voice metrics reveal severe distress (EDI of 78). Now AYA's constrained generative AI layer activates. Using only the voice-derived data and pre-trained clinical frameworks, the system generates a detailed clinical report—not a diagnosis, but a structured guide for clinicians grounded in evidence-based protocols.
Evidence and Validation
Evidence That Builds Trust
Our work isn't based on promises—it's grounded in rigorous, peer-reviewed research proving that voice AI can accurately detect mental health conditions, support trauma recovery, and save lives. These studies validate what frontline workers and patients already know: technology guided by compassion works.
An AI-enabled, trauma-informed rehabilitation protocol for Ethiopian women with complex trauma
Alemu, Y., Ohiomoba, P., Kahsay, Y., et al.
International Journal of Psychiatry Research • 2026
Key Findings
✓AI-enabled screening and rehabilitation protocol for trauma survivors
✓Effectiveness in addressing complex trauma from sex work, homelessness, and severe poverty
✓Integration with local mental health infrastructure
Implementing and analyzing the advantages of voice AI measurement-based care to address behavioral health treatment disparities among youth
Alemu, Y., Cárdenas Bautista, E., Vinson, S., Ohiomoba, P., et al.Telehealth and Telemedicine Today • 2024
Key Findings
✓Voice AI measurement-based care reduces health disparities in youth mental health
✓Implementation evidence for scaling in underserved communities
✓Improved treatment outcomes through objective severity monitoring
Objectively quantifying pediatric psychiatric severity using artificial intelligence, voice recognition technology, and universal emotions: Pilot study
Alemu, Y., Teshome, S., Salegh, E., Ohiomoba, P., & Vinson, S.
Annals of Research Protocols • 2023
Key Findings
✓Voice AI accurately quantifies psychiatric severity in pediatric populations
✓Universal emotional recognition improves diagnostic accuracy
✓Pilot validation across diverse populations
Objectively quantifying pediatric psychiatric severity using AI and voice recognition technology
Caulley, D., Alemu, Y., Burson, S., et al.
JMIR Research Protocols • 2023
Key Findings
✓Validated AI and voice recognition methodology for psychiatric assessment
✓High accuracy in identifying clinical severity levels
✓Scalable approach for global mental health screening
Our Team
Yared Alemu, Ph.D.
Co-Founder/CEODriven by a vision to build something meaningful, Dr. Alemu brings a rare blend of strategic leadership, clinical expertise, and hands-on innovation. He sets the direction and standard for everything we do.
Patrick Ohiomoba, MS
Co-Founder/CTOFocused, innovative, and driven by results, Patrick leads AYA’s AI product strategy with both technical depth and practical vision. As CTO, he translates complex ideas into scalable solutions, guiding the development of AI products that are purposeful, effective, and built for real-world impact.
Abdi Degefu, MD
Experienced, collaborative, and deeply grounded in implementation, Dr. Abdi Degefu plays a key role in translating AYA’s vision into real-world impact. As an implementation partner, he helps drive effective deployment, local coordination, and practical execution in the settings where the work matters most.
Implementation Director
Yoel Asfaha, MD
Compassionate, experienced, and clinically grounded, Dr. Yoel Asfaha leads AYA’s mental health services with a strong focus on quality, consistency, and impact. As Lead Mental Health Clinician, he helps ensure that care delivery remains practical, responsive, and aligned with the needs of the individuals and communities we serve.
Lead Mental Health ClinicianLet’s Work Together
