An AI-first, Gen Z–oriented fashion styling app enabling users to upload wardrobe items, receive personalized outfit suggestions using AI, and engage socially via outfit polls and feeds. The solution leverages Firebase’s scalable cloud backend and integrates OpenAI for prompt-based outfit generation. Users can manage a virtual closet, receive AI alerts on missing wardrobe items, and interact with a community through polls and comments. It also includes an admin panel for moderation, analytics, and subscription management. Monetization is driven through subscription tiers and integrated ads. The product is designed as a progressive MVP with clearly defined “must-have” and “nice-to-have” features to facilitate phased rollout. Post-launch, the client aims to validate market fit and scale with affiliate shopping and influencer integrations.

The project involves building a SaaS-based web portal that enables restaurants to generate unique QR codes for each table and for takeaway orders. When scanned, these QR codes allow customers to view a digital menu, place orders, and select payment options such as PayNow or PayLater. The system provides restaurant owners with an admin panel to manage menus, orders, payments, and subscription plans.
Additionally, a mobile app was developed for restaurant staff to manage incoming orders, track payment status, and receive alerts. The platform includes customizable themes, reporting tools, and supports different subscription models.

This project focused on creating mapping reports to highlight geographic and linguistic disparities in OB/GYN service availability across Kansas. The objective was to provide visual evidence for healthcare researchers and policymakers to better understand provider distribution, identify underserved regions, and highlight language access barriers for Hispanic populations. The deliverables included static maps of provider clusters, Spanish-speaking access segmentation, and a custom symbolic visual to humanize the access challenge.