wavexnani 's Work | ContraWork by wavexnani
wavexnani

wavexnani

Full Stack Dev | Next.js + FastAPI + Mobile Apps

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Cover image for Built an automation tool that
Built an automation tool that converts Haskell scripts into fully formatted assignment documents by executing code, capturing outputs, and generating structured .docx files.
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A dark-themed Movies web app designed end-to-end in Figma — starting from low-fidelity wireframes through to a fully linked interactive prototype. Covers three screens: Home, Movie Detail, and Search. Full design process showcased — UX structure first, visual design second. Prototype is clickable and ready for handoff to development.
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Cover image for Silk Saree Store is a
Silk Saree Store is a full-stack e-commerce web app built for a traditional Indian silk saree brand, combining customer shopping flows with merchant and delivery operations in a single product. I built the frontend with Next.js, TypeScript, and Tailwind CSS, and integrated it with a Python Flask + PostgreSQL backend through production-style REST APIs. Key implementation highlights include role-aware authentication, merchant product management (CRUD + stock controls), buyer cart-to-order flow, and delivery status orchestration. This project demonstrates the kind of work I deliver for e-commerce platforms, product-led businesses, and traditional brands moving to digital commerce.
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Cover image for Pokedex is a mobile app
Pokedex is a mobile app for Pokemon fans to discover Pokemon, view detailed stats and descriptions, and manage their own captured collection. It connects to PokéAPI for live Pokemon data and also uses a custom backend for account, capture, favorites, and trading flows. What makes it stand out is the polished game-like UI, fast live search suggestions, and end-to-end experience from login to collection management.
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Cover image for This app helps college students
This app helps college students track subject-wise attendance quickly, understand how safe they are against the required attendance threshold, and avoid attendance shortages before exams. Users can mark classes in seconds, review per-subject history, and onboard faster by importing timetable/attendance data through OCR and QR flows. It is production-ready because it uses atomic SQLite transactions, optimistic UI with rollback/undo, local-first secure storage, notification scheduling, telemetry/error monitoring, and a complete onboarding-to-dashboard flow prepared for Play Store release.
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