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AI Course Learning Assistant Platform — Full-Stack RAG Application
Developed a full-stack AI-powered learning platform that allows students to create accounts, sign up, log in, and access personalized course learning resources.
Built an end-to-end Retrieval-Augmented Generation (RAG) system where students can upload lectures, PDFs, notes, and course materials for intelligent question answering.
Implemented semantic search and vector-based retrieval pipelines using LangChain and embedding models to provide accurate, context-aware responses from uploaded content.
Designed AI-powered tutoring features that explain AI and Deep Learning concepts directly from course-specific materials instead of relying on generic answers.
Integrated automatic quiz generation, practice assessments, and instant feedback based on lecture content to improve student engagement and knowledge retention.
Developed secure authentication, user management, course management, file upload, and progress tracking functionalities for a complete learning experience.
Built scalable backend APIs for document processing, embedding generation, retrieval workflows, and LLM-powered response generation.
Created a responsive frontend dashboard enabling students to manage courses, upload materials, interact with the AI tutor, and take quizzes seamlessly.
Optimized document indexing and retrieval performance to ensure fast and relevant responses across large educational datasets.
Delivered a complete AI-driven educational platform combining Full-Stack Development, RAG, LangChain, Vector Databases, and Large Language Models (LLMs).
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🚀 Elevating customer support with intelligent design.
A modern AI-powered SaaS landing page crafted to simplify conversations, automate workflows, and create a seamless user experience. Focused on clean layouts, clear hierarchy, and conversion-driven UI that helps businesses scale support efficiently.
💡 Great design isn't just about aesthetics—it's about creating experiences that drive results.
📩 Available for SaaS, AI, Web App, and Dashboard UI/UX projects.
👉 Book a call: https://calendly.com/gopi-uiux/30min
👉 Dribble: https://dribbble.com/OptimityLogics
👉 Behance: https://www.behance.net/optimitylogics
👉 Portfolio: https://gopi-prajapati-portfolio.vercel.app
Great work 🔥
Try Verity is an AI-powered interview coaching platform that creates realistic interview simulations based on a candidate's actual resume and target job description.
For this challenge, I used Google Stitch as the center of a real product redesign workflow.
Instead of building a mockup from scratch, I imported screenshots from the existing product, generated redesigned interfaces, and used Stitch to transform those concepts into production-ready UI code.
My workflow:
• Existing Try Verity screens → AI redesign mockups
• Mockups imported into Google Stitch
• Stitch-generated UI and front-end structure
• Implementation and integration using Codex
• Integration into the real application
The goal was not to create a prototype, but to modernize an existing product while preserving functionality, workflows, and business logic.
The redesign covered the landing page, interview workspace, recruiter feedback experience, reporting dashboard, pricing pages, and onboarding flow.
Key improvements:
• Complete landing page redesign
• Interview workspace redesign
• Recruiter-style feedback experience
• Modern SaaS visual language
• Improved information hierarchy
• Better usability and readability
• Enterprise-grade UI patterns
Tools used:
• Google Stitch
• ChatGPT
• Codex
• Next.js
• React
• TypeScript
• Tailwind CSS
Application Web: https://www.tryverity.co/
Video Walkthrough:https://youtu.be/iITu8t9-5pw
Google Stitch became the bridge between visual exploration and implementation, allowing me to iterate much faster than a traditional design-to-development workflow.
Thanks to the Google Stitch team for building tools that make interface iteration dramatically faster.
Looks cool
Testing out some new tools today and ended up with this project. The core idea is a mashup between the classic Pokedex—specifically its ability to scan and display item rarity—and a high-end rare sneaker marketplace. Instead of Pokémon, it’s all about tracking and auditing sneaker data.
I started with a simple prompt and kept iterating by feeding it reference images, refining the details until it hit the right vibe.
For the interface, I went for a 'slideshow' feel using D-pad controls to interact with the cards. Honestly, it took me hours to get that button logic locked in—it’s not 100% pixel-perfect yet, but it works, and that’s a win for today! HEHE
The design leans into Neo-Retro Brutalism, blending 90s hardware sensibilities with modern UI patterns. Through a Skeuomorphic-System approach, the interface mimics a proprietary firmware environment—using a terminal-first aesthetic and data-dense layout to create a physical sense of 'system presence' rather than just a flat web page.
Overall, this tool is an absolute beast for brainstorming and visualizing web concepts. It’s been a game-changer for getting ideas out of my head and into a playable prototype. It really bridges the gap between 'just a static image' and 'a fully interactive system.
Beautiful ❤️
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