I developed Tribation SportTech, a mobile application aimed at transforming sports talent discovery and development by uniting athletes, coaches, trainers, mentors, and sports enthusiasts worldwide. The app leverages artificial intelligence to offer personalized recommendations, training programs, meal plans, and more. Users can showcase their talents, engage with others in the sports community, and access enhanced features through a monthly subscription. The project is slated for public release by the end of this year.

Tribation SportTech serves as an all-encompassing platform for the sports community. Users can create personalized profiles to highlight their skills, achievements, and interests. The app enables them to discover and connect with athletes, coaches, and sports professionals globally. By posting multimedia content, users can stand out and gain recognition within the community. The platform fosters engagement through direct messaging, following other users, and personalized feeds curated based on individual preferences and activities.

A key feature is the integration of AI-driven chatbots that provide customized training programs, meal recommendations, and personal coaching tips. Users can also explore and discover nearby trails in Ontario, Canada, using integrated map functionalities. They can start workouts on selected trails, track their performance, and create custom workout plans.

Tribation SportTech operates on a subscription model. Users can access the basic features for free, but by opting for a monthly subscription, they unlock premium features and enhanced functionalities within the app. This includes advanced AI recommendations, exclusive training programs, and additional networking opportunities.

The mobile application was developed using Flutter, ensuring compatibility with both iOS and Android platforms. Emphasis was placed on intuitive user interface design and a seamless user experience, allowing users to navigate the app effortlessly.

The backend was developed entirely in Rust, chosen for its performance and reliability. A microservices architecture was implemented to allow independent scaling and maintenance of different services. Key technologies and components include:

Database Management: PostgreSQL was utilized for its robustness in handling relational data. Redis was employed for caching and session management to enhance performance.

Media and Storage: Integrated S3 Object Storage for efficient handling of user-uploaded media files.

Communication and APIs: gRPC API endpoints facilitate efficient communication between the client and server. Kafka handles data streaming and real-time updates within the app.

Notifications: Firebase Cloud Messaging (FCM) was used to implement push notifications, keeping users informed about activities, messages, and updates relevant to them.

Artificial Intelligence: AI algorithms were developed to analyze user-generated content for compliance with terms of service, ensuring a safe and respectful community environment. The AI also powers chatbots that provide personalized recommendations and assistance to users.

A subscription model was implemented, allowing users to pay a monthly fee to unlock additional features and capabilities within the app. This includes access to premium content, advanced AI-driven insights, and exclusive training resources, enhancing the overall user experience.

Continuous Integration and Continuous Deployment (CI/CD) pipelines were established using Jenkins to automate testing and deployment processes. The application was deployed on Amazon Web Services (AWS), utilizing Elastic Kubernetes Service (EKS) for efficient management and scaling of microservices. Each microservice can be scaled independently based on demand, ensuring optimal performance and reliability.

An admin dashboard was developed using Next.js, TypeScript, and Material-UI (MUI). This dashboard allows administrators to manage user accounts, moderate content, and access analytics on platform usage. It provides tools to oversee the health and performance of services, ensuring smooth operation of the application.

In this project, I was responsible for the full-stack development, handling every aspect from initial conceptualization to deployment. My responsibilities included:

Requirement Analysis: Collaborated with the client to understand project goals and user needs, defining technical specifications and a project roadmap.

Architecture Design: Designed the system architecture with a focus on scalability, reliability, and security, selecting appropriate technologies to meet the project's requirements.

Frontend and Backend Development: Developed the user interface and experience, implemented backend services, databases, and APIs.

AI Integration: Developed and integrated AI components for content moderation and providing personalized user recommendations through chatbots.

DevOps: Set up CI/CD pipelines, deployed the application to AWS, and ensured the infrastructure is scalable and secure.

Quality Assurance: Conducted thorough testing, including unit tests and integration tests, to ensure the application functions correctly and efficiently.

Maintenance and Monitoring: Established monitoring tools and procedures to maintain the application's performance and reliability post-deployment.

To ensure the application could handle a growing user base, I implemented a microservices architecture and deployed the backend on AWS EKS. This setup allows services to scale independently based on load, ensuring high availability and optimal performance as the number of users increases.

Maintaining fast response times was critical for user satisfaction. I optimized database queries, used Redis for caching, and streamlined API communications. These optimizations resulted in a smooth user experience, even as the app's feature set expanded.

Effective content moderation was essential to maintain community standards. I developed AI algorithms to automatically analyze and flag inappropriate content, ensuring a safe environment for all users. This automated system allows for swift enforcement of the terms of service without the need for constant manual intervention.

Integrating a subscription model required balancing revenue generation with user satisfaction. I implemented a system where users have access to essential features for free, encouraging wide adoption. The monthly subscription unlocks premium features, providing additional value for paying users without restricting the core functionality for others.

Programming Languages: Rust, Dart (Flutter), TypeScript

Frameworks and Libraries: Tonic, Flutter, Next.js, Material-UI (MUI)

Databases and Storage: PostgreSQL, Redis, AWS S3

DevOps and Cloud Services: AWS (EKS, S3), Jenkins, Docker, Kubernetes

Communication and Messaging: gRPC, Kafka, Firebase Cloud Messaging (FCM)

Artificial Intelligence: OpenAI, Gemini

The development of Tribation SportTech resulted in a robust mobile application that provides a dynamic platform for the sports community to connect, engage, and develop their talents. The integration of AI-driven recommendations, personalized user experiences, and a subscription model for premium features positions the app to make a significant impact in the sports industry. The scalable architecture and thorough testing ensure that the application is ready to handle a wide user base upon its public release.

This project showcases my ability to manage complex full-stack development tasks, integrate advanced technologies like AI, and deliver a comprehensive solution that meets both client and user needs. By bringing together various technologies and focusing on user-centric design, the application is set to offer valuable experiences to its users and create opportunities for growth and development within the sports community.