Scalable Telehealth Platform for On-Demand Mental Health Services
What was at stake
The startup had validated demand through a basic MVP but was hitting scalability walls — their monolithic backend couldn't support concurrent video sessions beyond 500 users, therapist matching was entirely manual, and patient no-show rates were hovering at 38%. They needed a platform that could scale to tens of thousands of monthly sessions while delivering the intimacy and reliability that mental health care demands.
How we delivered
Real-Time Communication Infrastructure
Architected a WebRTC-based video and audio pipeline with adaptive bitrate switching, automatic fallback to audio-only on degraded connections, and end-to-end encryption. Built a custom signaling server on Node.js capable of handling 10,000+ concurrent sessions with sub-100ms connection establishment.
AI-Powered Therapist Matching Engine
Developed a matching algorithm that factors in patient intake assessments, therapeutic modality preferences, insurance coverage, availability windows, and historical outcome data. The system continuously learns from session ratings and completion rates to improve match quality over time.
Engagement & No-Show Prevention System
Built a multi-channel reminder and engagement system using push notifications, SMS, and email with intelligent timing based on patient behavior patterns. Integrated a waitlist backfill mechanism that automatically offers cancelled slots to other patients within minutes.
Compliance & Clinical Workflow Automation
Implemented HIPAA-compliant data storage with encryption at rest and in transit, audit logging for every data access event, and automated session note generation using speech-to-text and NLP summarization — reducing post-session documentation time by 70% for therapists.
Measurable impact, verified by the client
Technologies we used
“TPWITS transformed our scrappy MVP into a platform that therapists and patients genuinely love. The AI matching alone cut our manual scheduling overhead by 80%, and our no-show rate dropped from 38% to under 15%. They understood the sensitivity of mental health care and built accordingly.”
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