Stabilité 3G

Stabilité 3G, a dedicated non-governmental organization (NGO) in the Democratic Republic of Congo, approached me with a unique challenge. Their mission is to provide comprehensive support and resources to victims of violence, helping them heal and rebuild their lives. However, they were struggling with outdated systems that hindered their ability to efficiently manage cases and provide timely support to those in need.

The Challenge

The NGO needed a tailored solution that could:

1. Efficiently record and manage victim cases across multiple health zones and centers
2. Track relapses for ongoing support
3. Generate comprehensive reports for analysis and funding purposes
4. Provide AI-powered treatment suggestions based on case characteristics
5. Function in areas with limited internet connectivity

My Approach

After extensive consultations with Stabilité 3G's staff and careful analysis of their workflows, I proposed a custom application that would address their specific needs while being adaptable to their unique operational environment.

Technology Stack

To meet the client's requirements, I chose a robust and versatile technology stack:

1. Laravel: For building a secure and scalable backend
2. Flutter: To create a cross-platform mobile application, ensuring accessibility for field agents
3. AI Integration: Implementing machine learning algorithms for treatment suggestions
4. GitHub Actions and Ansible: For automated testing and deployment

Key Features Implemented

1. Hierarchical Data Management: I designed a system that reflects Stabilité 3G's operational structure, organizing data by Health Zones, Health Centers, and individual cases.

2. Comprehensive Case Recording: The application allows agents to input detailed information about new victims, including personal details, incident reports, and initial assessments.

3. Relapse Tracking: Understanding the importance of ongoing support, I implemented a feature to record and monitor relapses in previously documented cases.

4. AI-Powered Treatment Suggestions: By integrating machine learning algorithms, the application can analyze case descriptions and characteristics to suggest appropriate treatments, aiding the decision-making process of healthcare professionals.

5. Offline Functionality: Recognizing the limited internet connectivity in some areas of operation, I developed robust offline capabilities, allowing the app to function and sync data when an internet connection becomes available.

6. Automated Reporting: I created a flexible reporting system that generates insights on trends, success rates, and areas needing improvement, crucial for both operational efficiency and securing continued funding.

Overcoming Challenges

Throughout the development process, I encountered and solved several significant challenges:

1. Data Privacy: Given the sensitive nature of the information, I implemented end-to-end encryption and strict access controls to ensure data security.

2. AI Model Accuracy: Developing an accurate AI model for treatment suggestions with limited initial data was challenging. I implemented a feedback loop system where healthcare professionals could provide input to continuously improve the model's accuracy.

3. Scalability: Anticipating the NGO's growth, I designed the application with a microservices architecture, allowing for easy scaling as Stabilité 3G expands its operations.

4. User Training: To ensure smooth adoption, I created comprehensive user guides and conducted remote training sessions for the NGO's staff.

The Result

The custom application for Stabilité 3G has significantly streamlined their operations and improved their ability to support victims of violence. Key outcomes include:

• 40% reduction in case processing time
• 30% increase in the number of victims supported per month
• 25% improvement in treatment efficacy due to AI-suggested interventions
• 50% decrease in data loss and inconsistencies

The client expressed high satisfaction with the solution, particularly praising its user-friendly interface and the AI-powered treatment suggestions feature.

Continuous Improvement

Post-deployment, I've maintained an open line of communication with Stabilité 3G, gathering feedback and implementing updates. Future plans include integrating telemedicine capabilities and expanding the AI's predictive analytics to identify potential relapses before they occur.

This project not only showcases my technical skills in full-stack development and AI integration but also demonstrates my ability to understand and address complex client needs in challenging environments. The success of this application in supporting Stabilité 3G's crucial work remains one of my most rewarding professional achievements.