Loading...
Mayart Candles is a full-stack e-commerce application built with React 18 and TypeScript on the frontend, connected to a robust Express.js and MongoDB backend. The platform enables customers to browse, search, and purchase handmade candles with extensive customization options including color selection, fragrance choice, and size preferences. The backend provides RESTful APIs for candle browsing, filtering by category/size/type, shopping cart management, order processing, and admin functionalities. Authentication is handled via JWT tokens, with Bcryptjs for password security. The project demonstrates enterprise-level patterns including server-side data loaders, async state management, and comprehensive form validation.
Initialized React application with Tailwind CSS and TypeScript configuration. Set up project structure with Create React App, installed essential dependencies including React Router v6, Tailwind CSS, and Material-UI for component framework.
Developed responsive navigation bar and footer for mobile, tablet, and desktop breakpoints. Implemented animated mobile menu with side navigation, desktop menu variants, and action buttons for shopping cart and favorites.
Created comprehensive candle product data types and MongoDB schema. Implemented product browsing with Mongoose models supporting colors, fragrances, sizes, pictures, and pricing with sale price support.
Added product search bar with autocomplete thumbnails, multi-parameter filtering by shape/color/size/fragrance/price range, and sort options. Implemented dynamic filter extraction from product catalog and responsive filter/sort UI components.
Developed shopping cart with quantity adjustment, item persistence using browser local storage, favorites/wishlist functionality, and shopping cart popover overlay. Implemented proper state management with quantity increment/decrement and item removal.
Built comprehensive admin dashboard with collapsible order tables using Material-UI Table components. Implemented order detail viewing with itemized candle breakdown, total price calculation, order deletion, and JWT-protected API endpoints.
Enterprise-grade AI-powered recruitment platform with voice interviews, resume screening, multi-channel communication, and seamless ATS/HRIS integrations. Automates hiring workflows for Quick Service Restaurants, healthcare, and construction industries.
A production-ready computer vision model that detects and classifies hands, arms, and non-hand objects in real-time with 96% accuracy.
Local-first memory layer for AI coding agents. 14 MCP tools, 268K+ indexed chunks, hybrid semantic+keyword search, local LLM enrichment. pip install brainlayer.
Local voice input/output layer for Claude Code. 7 MCP tools, 5 voice modes, whisper.cpp STT (~300ms), edge-tts, session booking. bunx voicelayer-mcp.