In this video, I demonstrate a complete e-book publishing workflow:
• login
• social feed
• Canvas e-book editor
• external book download
• full book import
• product publishing
• product detail
• personal digital library
• PDF / EPUB / TXT / JSON / .trezzo exports
• real reading of the exported book
• source code preview of the CanvasEbookEditor
Built with:
• Vue 3
• Vite
• Node.js
• Express API
• MongoDB / Mongoose
• custom Canvas e-book editor
• digital product publishing flow
• personal library system
• PDF / EPUB / TXT / JSON export pipeline
• custom .trezzo export format
• production domain via Cloudflare tunnel
This is not a generated AI template, a pre-made website, or a static mockup.
It is a custom-built SaaS workflow developed through real frontend and backend code, with a working editor, publishing system, product detail, personal library and export pipeline.
Playmaker Xpress – Full-Stack Fitness & Training Platform
I designed and developed Playmaker Xpress, a full-stack website for a personal training and athletic performance business.
I built the frontend using Next.js, React, and TypeScript, with FastAPI powering the backend and PostgreSQL for the database.
The platform provides a responsive, modern experience where clients can explore services including personal training, speed training, movement training, group fitness, and kickboxing fitness.
This project demonstrates my ability to build both the frontend and backend of a real-world web application, connect APIs to a database, and deploy a production-ready application.
I’m available for full-stack, React, Next.js, Python, and FastAPI development project
Built an AI-powered customer support automation workflow that can classify incoming emails, identify support requests, retrieve relevant information from a knowledge base, and assist with generating the right response.
The workflow combines AI agents, RAG, embeddings, Pinecone, Gmail, and automated notifications to reduce repetitive support work while keeping human review in the loop.
The flow includes:
📩 Incoming email detection
🤖 AI-based support request classification
📚 Knowledge base retrieval with Pinecone
🧠 Context-aware customer support agent
✍️ Automated response draft generation
🔔 Reviewer notification through Telegram
⚡ Separate handling for non-support emails
I’ve been exploring more ways to combine AI + automation + real-world business workflows, rather than using AI only as a chatbot.