Android Application for Behavioral Health Training & Certification

EBPI Behavioral Health Online is an Android-based learning management system (LMS) designed to deliver targeted educational content to Behavioral Health staff. The application offers comprehensive training and certification modules in critical topics such as:

• Alternatives to Seclusion, Restraint, and Timeout
• HIPAA Compliance
• Confidentiality and Informed Consent
• Client Rights and Responsibilities
• Abuse, Neglect, and Exploitation
• Person-Centered Planning
• Cultural Competency
• Documentation Standards
• Incident Reporting
• …and more.

The EBPI curriculum is approved by the state of North Carolina for training in alternatives to restraint, seclusion, and timeout.

We handled the full lifecycle of the application—from planning and system architecture to development and deployment. The backend is powered by a Python/Flask API hosted on a Linux server, utilizing NGINX as the web server and reverse proxy, containerized with Docker Compose. The API facilitates communication between the mobile application and its companion web portal. The Android application itself was developed using Android Studio with Kotlin.

Technologies Used:

• Android Studio
• Kotlin
• Docker
• Python
• Flask
• MySQL
• Google Cloud

Responsive WordPress Website for a North Carolina-Based Clinic

We developed a custom website for a health care clinic located in North Carolina, built on the WordPress platform to ensure ease of content management and scalability. The site provides essential information about the clinic’s services, staff, and contact options, while offering a user-friendly experience across desktop and mobile devices.

The project included front-end customization using HTML, CSS, and PHP to align with the clinic’s branding and functional requirements. A MySQL database powers the site’s dynamic content and data storage.

Technologies Used:

• WordPress
• HTML / CSS / PHP
• MySQL

Conversational Triage System for Virtual Care and Emergency Guidance

We designed and implemented an enhanced workflow for a virtual Clinical Assistant, transforming it into a more open-ended, symptom-driven triage tool. The assistant begins by asking users about their current symptoms, then dynamically guides them through a tailored series of follow-up questions.

Based on user responses, the system determines whether the individual should be directed to the Emergency Room or if a Virtual Appointment is appropriate. When applicable, the assistant can either initiate appointment scheduling or urge the user to seek immediate emergency care.

This project was developed as a demonstration piece and showcased at a major technology convention to highlight the potential of AI-driven solutions in digital healthcare.

Key Capabilities:

• Symptom-based conversational flow
• Dynamic triage logic
• Emergency vs. virtual care decision-making
• Integration-ready appointment scheduling triggers

Skills/Technologies used:

• AI Prompt Engineering
• Unreal Engine
• C++
• Microsoft Azure
• AI Chat bots