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Built GymFlow — a multi-tenant gym management SaaS using Python, React, and Flutter. Supports multiple gym branches from a single platform with member management, attendance, diet plans, and scheduling across web and mobile.
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Connect with clients, get discovered, and run your business 100% commission-free
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Introducing Job Board Hub, a full-stack application built with the MERN stack to explore remote job opportunities across different areas such as technology, design, marketing, and more.
The main idea behind the app is to help users find job opportunities and quickly understand whether a position fits their profile.
One of the main features is AI Job Summary, an artificial intelligence integration that generates summaries of long job descriptions. Many job posts often include lengthy text, mixed requirements, and repetitive information, so the goal was to improve the user experience and make reading faster and clearer.
Beyond the visible feature, this project also allowed me to work on important backend decisions:
- AI integration through an AI Gateway
- The possibility to switch or combine models in the future
- Rate limiting to prevent abuse and control token usage
- Streaming responses to improve the perception of speed
- Clean backend architecture within a MERN app
- Organization of remote jobs by categories
The focus was not just to “add AI,” but to integrate it in a more thoughtful way: considering costs, user experience, scalability, and system control.
Job Board Hub is a simple app in concept, but it helped me demonstrate how an AI feature can provide real value when supported by good backend decisions.
I’m very happy with this project because it combines product, backend, and artificial intelligence into a useful and easy-to-understand experience.
#MERN #FullStackDevelopment #ArtificialIntelligence #BackendDevelopment #React #NodeJS #MongoDB #ExpressJS #AIIntegration #WebDevelopment
Built a responsive and visually appealing e-commerce website to promote and sell Lifestyle Watch products.
Zappy: Building a Real-Time Workflow Layer for WhatsApp-Based Businesses
Zappy is a mobile first shared WhatsApp inbox for small businesses, designed to turn chaotic customer messaging into structured team workflows.
The core problem is not messaging, but coordination. As small teams grow, conversations become fragmented, messages are missed, and there is no clear ownership or system of work.
I designed Zappy as a real time, multi tenant communication system where every business operates in an isolated workspace, and every conversation is structured, trackable, and assignable across team members.
The system is built with a contract first architecture using OpenAPI and shared types, ensuring the backend and mobile app stay fully in sync as the product scales.
Real time updates are handled through Socket.IO, with fallback polling for reliability across environments.
On top of this communication layer, AI is embedded directly into workflow moments, not as a separate tool. It assists with reply suggestions, conversation summaries, tone rewriting, sentiment detection, and off hours responses, all aimed at reducing cognitive load and response time for small teams.
Zappy is ultimately a workflow layer for WhatsApp based businesses, focused on structure, speed, and clarity in customer communication.
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