Sora Ai — Frontend Development, built by Subhan Nadeem
AI · Frontend

Sora Ai

Frontend Development

Designed and built by Subhan Nadeem.

Role
Design & development
Built by
Subhan Nadeem

Overview

The platform is a user-centric frontend application for AI video generation, enabling users to create accounts, top up balances, and generate videos using reference images or videos. It features a responsive, mobile-friendly design with dark and light modes. Users can manage their generated videos, view invoices, and monitor costs efficiently. The dashboard provides streamlined navigation with a sidebar, balance overview, and settings. Top-up and video generation flows include clear cost breakdowns and step-wise guidance, ensuring a seamless, secure, and intuitive experience for all users.

More projects

All projects
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AI · SaaS

ChatAI

Create Custom Chatbot SaaS Platform

A modern SaaS solution developed with Next.js, Supabase, TypeScript, LangChain, and OpenAI API, empowering users to create fully personalized AI chatbots. Users can design chatbots by customizing names, avatar, chat starters, personas, and instructions during a seamless onboarding process. The platform allows content uploads via PDF, enabling chatbots to deliver responses based on user-provided data. With built-in authentication (signup/login), Stripe payment integration, and a user-friendly dashboard for managing chatbot settings, users can easily fine-tune their chatbots. Each chatbot comes with a unique URL for effortless integration into any website.

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Pod Transcripts AI Chatbot Application, built by Subhan NadeemLive
AI · Chatbot

Pod Transcripts AI Chatbot Application

Podcast Transcript AI Chatbot using Vercel AI SDK, Langchain & Supabase. I built a smart AI chatbot for a podcast website featuring popular episodes with detailed transcripts. The chatbot uses Vercel AI SDK, Langchain, and Supabase vector database for efficient and accurate responses. Key Features: Natural Language Querying: Users can ask questions in natural language, and the chatbot responds using data stored from podcast transcript PDFs. Contextual Answers: Uses Langchain and embeddings to understand and respond with accurate information sourced from stored vectors in Supabase. Related Podcast Recommendations: In addition to answering questions, the chatbot suggests relevant podcast episodes with clickable links that navigate directly to the episode’s transcript page. This solution is ideal for content-rich platforms like podcasts, video courses, or blogs that want to provide an interactive experience through AI-driven search and discovery.

Vercel SDK AILangchainNext.jssupabase
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Ralux Solar configurator: bill of materials step with project summary, built by Subhan Nadeem3Live
Solar · Configurator

Ralux Solar Configurator

Fullstack Application

Developed a comprehensive solar mounting system configurator with admin panel for Ralux Solar, designed to analyze location-based data and generate optimized solar mounting solutions. The platform intelligently suggests suitable mounting systems based on customer area, environmental conditions, and regional standards, ensuring structural reliability and cost efficiency. Engineered an advanced calculation engine in Node.js to handle diverse country-specific structural load formulas across 20+ mounting systems and their variants. Implemented interactive map drawing tools allowing users to select their installation area and place solar panels directly on the map. Automatically generated 2D mounting system layouts based on user inputs and panel configurations. Automated Bill of Materials (BOM) generation based on the configured design, providing cost and material breakdowns instantly.

Node JsNext.jssupabaseMantine UI+2
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