MindWell
Enterprise Healthcare Practice Management Platform with Microservices Architecture
Project Overview
MindWell is an enterprise-grade healthcare practice management platform built with modern microservices architecture. Designed specifically for mental health professionals, it handles the complete patient lifecycle from booking to billing, with advanced features for appointment management, digital prescriptions, multi-channel notifications, and subscription-based SaaS monetization.
Challenge
Building a healthcare SaaS platform with complex multi-role architecture, real-time synchronization, regulatory compliance, scalable subscription model, and multi-channel communication systems.
Solution
Implemented microservices architecture with Django REST Framework, React frontend, PostgreSQL database, Redis caching, Celery for async tasks, and Django Channels for real-time WebSocket communication.
Outcome
Achieved production-ready platform with <200ms API response times, 99.9% uptime target, multi-tenant SaaS design supporting 1000+ clinics, and comprehensive security with HIPAA-ready data handling.
Technical Architecture
Frontend Stack
- • React 18 with TypeScript
- • Redux Toolkit for state management
- • Material-UI component library
- • React Router for navigation
- • WebSocket for real-time updates
Backend Infrastructure
- • Django 5.0 with Django REST Framework
- • PostgreSQL with advanced indexing
- • Redis for caching and sessions
- • Celery for async task processing
- • Django Channels for WebSocket
- • JWT authentication with RBAC
Key Features
Appointment Management
Conflict detection, timezone handling, recurring appointments, real-time availability
Multi-Channel Notifications
SMS, Email, WhatsApp with delivery tracking and retry logic
Digital Prescriptions
PDF generation, medication tracking, pharmacy integration
Subscription Management
Tiered pricing, automated billing, feature gating, Razorpay integration
AdInvestor.co
Enterprise AI-Powered Advertising Platform with Real-Time Optimization
Project Overview
AdInvestor.co is a sophisticated advertising platform that leverages artificial intelligence to optimize ad campaigns in real-time. Built with enterprise-grade architecture, it handles millions of ad impressions daily while providing advanced analytics and automated bidding strategies.
Challenge
Building a scalable advertising platform that can process millions of real-time bidding requests while maintaining sub-50ms response times and providing AI-driven optimization.
Solution
Implemented microservices architecture with React frontend, Node.js backend, Redis caching, and TensorFlow.js for real-time AI optimization.
Outcome
Achieved 99.9% uptime, 50ms average response time, and 15% improvement in campaign performance through AI optimization.
Technical Architecture
Frontend Stack
- React 18 with TypeScript
- Redux Toolkit for state management
- Material-UI component library
- D3.js for advanced visualizations
Backend Infrastructure
- Node.js with Express framework
- MongoDB with Redis caching
- TensorFlow.js for AI optimization
- AWS ECS with auto-scaling
Development Timeline
Phase 1: Architecture & Planning
System design, technology selection, and microservices architecture planning
Duration: 2 weeksPhase 2: Core Development
Backend API development, database design, and frontend implementation
Duration: 8 weeksPhase 3: AI Integration
Machine learning model development and real-time optimization engine
Duration: 4 weeksPhase 4: Testing & Deployment
Comprehensive testing, performance optimization, and production deployment
Duration: 3 weeksSEPInsights.com
Advanced Patent Analytics Platform with Machine Learning Intelligence
Project Overview
SEPInsights.com is a comprehensive patent analytics platform that leverages advanced machine learning algorithms to provide competitive intelligence and IP portfolio management. The system processes millions of patent documents and provides real-time insights.
Challenge
Processing and analyzing millions of patent documents with complex legal language while providing real-time search and competitive intelligence insights.
Solution
Built custom NLP pipeline with Python, FastAPI, PostgreSQL, and machine learning models for patent classification and similarity analysis.
Outcome
Achieved 95% accuracy in patent classification, sub-second query times, and comprehensive competitive intelligence platform.
Machine Learning Pipeline
Data Processing
- Python with Selenium for web scraping
- BigQuery for large-scale data processing
- IP rotation for reliable data collection
- Real-time data synchronization
Analytics Engine
- Custom NLP models for patent analysis
- Elasticsearch for advanced search
- Real-time analytics dashboard
- Automated monitoring and alerting
Datatrics.com
Enterprise Customer Data Platform with Microservices Architecture
Project Overview
Datatrics.com is a sophisticated Customer Data Platform (CDP) built with microservices architecture. It handles massive data volumes with real-time processing, featuring specialized services for API, frontend, workbench, and targeting components.
Microservices Architecture
Frontend Stack (Vue.js)
- Vue.js 2.6.10 with Element UI
- Highcharts for data visualization
- Vue-i18n for internationalization
- Sentry for error tracking
Backend Infrastructure
- PHP 7.4 with Symfony framework
- MongoDB with Redis caching
- Docker containers with Kubernetes
- GeoIP integration for location data
Recent Development Insights
Production Optimizations
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Hotfix Implementation:
Fixed content display issues and Argentina region codes
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User Experience:
Enhanced demo project settings and integration installations
-
API Optimization:
Improved response times and project management features
Infrastructure Highlights
-
Containerization:
Multi-stage Docker builds with optimized PHP-FPM
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Data Processing:
Real-time event processing with advanced caching
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Analytics:
Advanced data visualization with Highcharts integration
ROAI, Paris
Advanced Freelance Platform with Django Backend and Production Deployment
Project Overview
ROAI is a sophisticated freelance platform built with Django and modern web technologies. Features advanced user management, real-time communication, and comprehensive project lifecycle management with production-ready deployment infrastructure.
Technical Implementation
Backend Architecture
- Django 3.2.13 with Gunicorn
- PostgreSQL with environment config
- WhiteNoise for static files
- Docker with Nginx proxy
Development Features
- Mobile-responsive design
- Email verification system
- Advanced user management
- Real-time communication
Recent Development Activity
Mobile Optimization
Enhanced navigation with breadcrumb improvements and responsive design
Email System
Comprehensive verification and notification system implementation
Production Deployment
Docker containerization with production environment configuration
AYLShop.com
Collaborative E-commerce Platform for Calma Properties
Project Overview
AYLShop is a collaborative e-commerce platform built for Calma Properties Inc., a collaborative team of architects, artists, builders, chefs, designers, engineers, and scientists. The platform showcases products from the Calma Family's diverse creative endeavors, featuring modern React frontend and Laravel backend with comprehensive AWS integration.
Challenge
Building a collaborative e-commerce platform that showcases diverse products from multiple creators while maintaining consistent user experience and seamless payment processing.
Solution
Implemented React.js frontend with Redux state management, Laravel backend with MySQL, AWS S3 for media storage, AWS SES for email, and PayPal integration for payments.
Outcome
Successfully launched platform enabling Calma Properties to showcase and sell products from their diverse creative team with seamless user experience and reliable payment processing.
Technical Stack
Frontend
- • React.js with Redux and Saga
- • Material-UI component library
- • Formik and Yup for form validation
- • SAAS for styling
Backend & Infrastructure
- • PHP Laravel framework
- • MySQL database
- • AWS EC2, SES, and S3
- • PayPal payment integration
- • PHPUnit for testing
SendOutpost.com
"Tinder for Startups and Investors" - Innovative Matching Platform
Project Overview
Outpost revolutionizes how startups and investors connect by eliminating traditional barriers like cold calling and email overload. Built as "Tinder for Startups and Investors," the platform uses innovative matching algorithms to facilitate meaningful connections between entrepreneurs and funding sources.
Challenge
Disrupting the traditional, inefficient process of startup-investor introductions through cold calling, LinkedIn messages, and email overload.
Solution
Built Django-based platform with matching algorithms, PostgreSQL database, Celery for async processing, Stripe integration, and Slack notifications for seamless communication.
Outcome
Created innovative platform that streamlines startup-investor connections, reducing friction and enabling more efficient fundraising and investment discovery.
Technical Implementation
Frontend Stack
- • Knockout.js for MVVM architecture
- • Bootstrap and Materialize CSS
- • Figma and Photoshop for design
- • SAAS for styling
Backend Infrastructure
- • Python Django with DRF
- • PostgreSQL database
- • Celery for async tasks
- • Digital Ocean deployment
- • Stripe payment processing
- • Slack integration for notifications
- • Python Nose for TDD
Photo Sharing App
Instagram for Web - High-Performance Photo Platform for Low Bandwidth
Project Overview
A high-performance photo sharing application prototype designed specifically for users with low bandwidth internet connections. Built with Indian users in mind, the app features intuitive UI/UX, fast responsive design, and optimized image processing to ensure blazing-fast uploads even on slow connections.
Challenge
Creating a photo sharing platform optimized for low bandwidth connections while maintaining fast upload speeds and responsive user experience.
Solution
Implemented in-memory image processing with Python, compressing and uploading images in three renditions to AWS S3, infinite scroll gallery, and dynamic loading for optimal performance.
Outcome
Achieved blazing-fast upload speeds even on low bandwidth, with intuitive UI/UX and responsive design that works seamlessly across devices.
Key Features
Frontend Features
- • Gallery module with infinite scroll
- • Dynamic photo loading on scroll
- • Fast and snappy slideshow feature
- • Date-grouped gallery organization
- • Drag and drop upload interface
- • Multiple file selection and simultaneous uploads
Backend Optimization
- • Python Django with DRF
- • In-memory image processing
- • Three renditions per image (compressed)
- • AWS S3 bucket storage
- • PostgreSQL database
- • Heroku deployment with Gunicorn
- • Python Pillow and Magic for image handling
Courier Software
Invoicing System for Courier Services with Automated Workflows
Project Overview
A comprehensive invoicing system designed and developed specifically for courier services, integrating automated workflows and ensuring robust data handling. The system streamlines operations for OM Sri Sai Service, providing efficient invoice management and tracking capabilities.
Challenge
Creating an invoicing system tailored for courier services that handles complex logistics workflows, automated calculations, and robust data management for high-volume operations.
Solution
Built full-stack invoicing application with automated workflows, comprehensive data handling, spreadsheet-like interface for easy data entry, and seamless integration with courier operations.
Outcome
Successfully streamlined courier service operations with automated invoicing, reducing manual work and ensuring accurate financial tracking for the business.
Key Features
Core Capabilities
- • Automated invoice generation
- • Spreadsheet-like interface for data entry
- • Automated workflow integration
- • Robust data handling and validation
- • Courier service-specific features
- • Financial tracking and reporting
Technical Highlights
- • Full-stack web application
- • Automated calculation engines
- • Data validation and integrity
- • User-friendly interface design
- • Scalable architecture
- • Production-ready deployment
Job Listing App
Software-as-a-Service Platform for Developer Job Listings
Project Overview
A complete Software-as-a-Service web application created for developer job listings, built with Ruby on Rails. The platform features modern SaaS architecture with subscription management, job posting capabilities, and comprehensive user management for both employers and job seekers.
Challenge
Building a SaaS platform for developer job listings that handles subscription management, user roles, job posting workflows, and scalable architecture for growth.
Solution
Developed with Ruby on Rails, implementing SaaS architecture with subscription tiers, PostgreSQL database, role-based access control, and modern web interface.
Outcome
Created a production-ready SaaS platform enabling developers and employers to connect through an efficient, scalable job listing system with subscription-based monetization.
Technical Implementation
SaaS Architecture
- • Ruby on Rails framework
- • PostgreSQL database
- • Subscription management system
- • Multi-tenant architecture
- • Role-based access control
- • Payment processing integration
Platform Features
- • Job posting and management
- • Developer profile system
- • Search and filtering capabilities
- • Application tracking
- • Email notifications
- • Admin dashboard
Video Streaming POC
Peer-to-Peer Video Streaming Proof of Concept
Project Overview
A proof of concept for peer-to-peer video streaming, exploring real-time communication technologies and WebRTC for distributed video delivery. This project demonstrates advanced web technologies for creating efficient, decentralized video streaming solutions without requiring traditional server infrastructure.
Challenge
Exploring peer-to-peer video streaming technologies to create efficient, decentralized video delivery without traditional server infrastructure, reducing bandwidth costs and improving scalability.
Solution
Implemented WebRTC-based peer-to-peer video streaming proof of concept using JavaScript, exploring real-time communication protocols and distributed video delivery mechanisms.
Outcome
Successfully demonstrated P2P video streaming capabilities, validating the concept for future implementation in production systems requiring efficient, scalable video delivery.
Technical Highlights
Core Technologies
- • JavaScript for real-time communication
- • WebRTC for peer-to-peer connections
- • P2P architecture design
- • Real-time video streaming
- • Distributed network protocols
- • Low-latency video delivery
Key Features
- • Peer-to-peer video streaming
- • Real-time communication
- • Decentralized architecture
- • Reduced server bandwidth costs
- • Scalable video delivery
- • Proof of concept validation
Django BigQuery Ad Project
Advertising Analytics Platform with Google BigQuery Integration
Project Overview
An advertising analytics platform built using Python Django and Google BigQuery for processing large-scale ad campaign data. The system enables efficient analysis of massive datasets, generating actionable insights for advertising campaigns and optimizing performance metrics.
Challenge
Processing and analyzing massive ad campaign datasets efficiently, generating insights from large-scale advertising data while maintaining performance and scalability.
Solution
Integrated Django framework with Google BigQuery for handling large-scale data processing, implementing efficient query patterns and analytics pipelines for ad campaign insights.
Outcome
Created scalable analytics platform capable of processing massive ad datasets, generating actionable insights and optimizing campaign performance through data-driven decisions.
Technical Architecture
Backend Stack
- • Python Django framework
- • Google BigQuery integration
- • Large-scale data processing
- • Efficient query optimization
- • Analytics pipeline development
- • Performance optimization
Analytics Capabilities
- • Ad campaign data processing
- • Large dataset analysis
- • Performance metrics calculation
- • Insight generation
- • Scalable query execution
- • Real-time analytics
PPP Salary Converter
Real-Time Purchasing Power Parity Tool for International Salary Comparisons
Project Overview
A production-grade, client-side web application for converting salaries between countries using Purchasing Power Parity (PPP) data from the World Bank. Built for international job seekers, remote workers, researchers, and professionals who need accurate salary comparisons that account for purchasing power, not just exchange rates.
Challenge
Creating an accurate salary conversion tool that accounts for purchasing power parity, not just exchange rates, while handling real-time data from multiple sources and providing research-grade accuracy for 200+ countries.
Solution
Built client-side application using World Bank ICP-2021 PPP data with CPI extrapolation, live currency exchange rates from ECB/Frankfurter, and comprehensive fallback systems for maximum accuracy and reliability.
Outcome
Created production-grade tool used by international professionals, researchers, and businesses for accurate salary comparisons with complete transparency in methodology and data sources.
Key Features
Core Functionality
- • Real-time PPP conversion using ICP-2021 data
- • CPI extrapolation for current year values
- • Live currency exchange rate comparison
- • 200+ countries with automatic fallback
- • Two PPP baskets (private consumption & GDP)
- • Complete methodology transparency
Advanced Features
- • Data export (JSON with methodology)
- • Share results with social integration
- • Conversion history (50+ saved)
- • Dark/light mode with system preference
- • Mobile-first responsive design
- • WCAG accessibility compliance
Technical Implementation
Frontend Stack
- • Vanilla JavaScript (ES2020+)
- • Tailwind CSS for styling
- • Tom Select for dropdowns
- • LocalStorage for persistence
- • Progressive Web App features
- • Offline capability with caching
Data Sources & APIs
- • World Bank API (PPP & CPI data)
- • ECB via Frankfurter API (live FX)
- • REST Countries API (country data)
- • Comprehensive fallback systems
- • Real-time data synchronization
- • Error handling and retry logic
RAG Personal AI
Fully Local, Private ChatGPT Clone with Retrieval-Augmented Generation
Project Overview
A fully local, private AI assistant built using Retrieval-Augmented Generation (RAG) that allows you to feed your own data (PDFs, notes, documents) into a local LLM. The system never leaves your machine, providing privacy-first AI without vendor lock-in, token costs, or data security concerns.
Challenge
Building an AI assistant that provides accurate, context-aware responses without using external APIs, while maintaining privacy and avoiding token costs or vendor lock-in.
Solution
Implemented RAG architecture using Ollama for local LLM inference, Qdrant vector database for semantic search, FastAPI backend, and LangChain for orchestration, enabling fully offline AI with document grounding.
Outcome
Created a production-ready local AI system that processes documents, answers questions with context from your data, and runs entirely offline—perfect for privacy-sensitive domains like healthcare, law, or enterprise.
Technical Architecture
RAG Pipeline
- • Document loading (PDF, Markdown)
- • Text chunking with overlap
- • Embedding generation (Sentence Transformers)
- • Vector storage (Qdrant)
- • Semantic search retrieval
- • Context-augmented prompting
Technology Stack
- • FastAPI for REST API
- • Ollama for local LLM (Mistral/LLaMA)
- • Qdrant vector database
- • LangChain for orchestration
- • Docker for containerization
- • GPU/CPU support
WebGL RPG Game
Low Poly Survival Game - A Technical Passion Project
Project Overview
A technically challenging low poly RPG survival game built with Unity and C# as a weekend project. This project demonstrates full-stack game development skills, from game logic and physics to browser deployment. Built with passion and attention to technical detail, showcasing capabilities in game development, 3D graphics, and WebGL optimization.
Challenge
Building a complete RPG survival game with inventory systems, physics interactions, collision detection, and rigid body dynamics, then optimizing it for WebGL browser deployment within a weekend timeline.
Solution
Leveraged Unity game engine with C# scripting, implementing low poly art style for performance, complete game systems (inventory, physics, interactions), and WebGL build optimization for browser deployment.
Outcome
Successfully created a playable RPG survival game running in browser, demonstrating technical skills in game development, 3D graphics, physics simulation, and WebGL optimization—all accomplished in a weekend.
Technical Implementation
Game Systems
- • Inventory management system
- • Item interaction and pickup
- • Collision detection algorithms
- • Rigid body physics
- • Survival mechanics
- • Low poly 3D graphics
Technical Stack
- • Unity game engine
- • C# scripting for game logic
- • WebGL build target
- • Browser deployment optimization
- • 3D graphics and rendering
- • Physics simulation
India Work Landscape
Interactive Data Thesis - India's Work & Earning Landscape
Project Overview
A comprehensive, interactive data thesis cataloging India's work and earning landscape. Built by Ahmad W Khan, this research tool provides an India-specific catalog of ways to earn: jobs, gigs, professional practices, MSMEs, and more, ranked by Entry Accessibility and Composite Sustainability metrics.
Challenge
Creating a comprehensive, interactive research tool that catalogs and visualizes India's diverse work and earning landscape with complex filtering, ranking systems, and data export capabilities.
Solution
Built interactive data visualization platform using Chart.js, PapaParse for CSV handling, advanced filtering algorithms, ranking systems based on Entry Accessibility and Composite Sustainability, with print/PDF export functionality.
Outcome
Created comprehensive research tool used by researchers, job seekers, and policy makers. Features master taxonomy, interactive charts, CSV export, and print functionality for academic and professional use.
Key Features
Data & Analysis
- • Master taxonomy of work types in India
- • Entry Accessibility scoring (0-100%)
- • Composite Sustainability metrics
- • Automation risk assessment
- • Capital requirement analysis
- • Income potential tracking
Technical Implementation
- • Chart.js for data visualization
- • PapaParse for CSV parsing
- • Advanced filtering and search
- • URL-shareable state management
- • Print/PDF export functionality
- • Responsive design for all devices
- • Research-grade data accuracy
FIRE Calculator
Financial Independence Retire Early (FIRE) Calculator by Ahmad W Khan
Project Overview
A financial planning tool created by Ahmad W Khan for fellow investors. The FIRE Calculator helps users determine their Financial Independence and Retire Early (FIRE) goals by calculating required corpus and age at FIRE based on monthly expenses, current age, current corpus, and expected investment returns.
Challenge
Creating an intuitive financial calculator that accurately computes FIRE goals across multiple currencies, with interactive sliders and real-time updates for user-friendly financial planning.
Solution
Built client-side JavaScript calculator with synchronized slider and input controls, multi-currency support (INR, USD, Euro), FIRE formula implementation, and real-time result calculation and display.
Outcome
Created free, accessible financial planning tool used by investors worldwide. Helps users plan for financial independence with accurate calculations and intuitive interface.
Key Features
Calculator Features
- • Monthly expense input with slider
- • Current age and corpus tracking
- • Expected annual return percentage
- • Required corpus calculation
- • Age at FIRE determination
- • Multi-currency support (INR, USD, Euro)
User Experience
- • Interactive sliders with number inputs
- • Real-time calculation updates
- • Clean, intuitive interface
- • Mobile-responsive design
- • Free, accessible tool for all
- • No account required
GetOffYourAss
Motivational Activity Generator - FindMeActivity by Ahmad W Khan
Project Overview
A motivational activity suggestion tool designed to help users overcome boredom and find inspiration. Created by Ahmad W Khan, GetOffYourAss (FindMeActivity) provides a curated collection of uplifting activities with beautiful UI to inspire positive action and improve mental well-being.
Challenge
Creating a tool that helps users overcome boredom, low motivation, and mental blocks by providing curated, actionable activity suggestions in an engaging, beautiful interface.
Solution
Built motivational activity generator with curated activity database, random suggestion algorithm, beautiful UI with animations, and focus on mental wellness and positive action.
Outcome
Created accessible wellness tool that helps users find motivation and overcome boredom. Features curated activities designed to uplift mood and inspire positive action.
Key Features
Core Functionality
- • Random activity suggestion generator
- • Curated collection of uplifting activities
- • Beautiful, engaging user interface
- • Animation and visual effects
- • Mental wellness focus
- • Mobile-responsive design
User Experience
- • Simple, intuitive interaction
- • Instant activity suggestions
- • Focus on positivity and motivation
- • Self-care and mental health support
- • Free, accessible tool
- • No account required
Your Life in Weeks
Life Calendar Visualization Tool - Inspired by Tim Urban's Concept
Project Overview
A life calendar visualization tool inspired by Tim Urban's "Your Life in Weeks" concept. Built by Ahmad W Khan, this tool helps users visualize their life in weeks (approximately 4,000 weeks), add milestones, track progress, and generate custom wallpapers for reflection and mindfulness.
Challenge
Creating an intuitive visualization tool that represents a person's life in weeks (4,000 weeks), allows milestone tracking, and generates exportable wallpapers for reflection and mindfulness.
Solution
Built React/TypeScript application with week-by-week visualization, milestone management system, html2canvas for wallpaper generation, interactive calendar interface, and export functionality.
Outcome
Created powerful mindfulness and reflection tool that helps users visualize their life journey, track milestones, and generate personalized wallpapers for daily motivation and perspective.
Key Features
Visualization Features
- • Week-by-week life calendar (4,000 weeks)
- • Color-coded weeks (filled, future, custom)
- • Milestone tracking and labeling
- • Interactive hover tooltips
- • Progress visualization
- • Age-based calculation
Technical Implementation
- • React with TypeScript
- • Tailwind CSS for styling
- • html2canvas for wallpaper export
- • Responsive design
- • Local state management
- • Smooth animations and transitions