Mohammed Imtiyaz

I designed and built an AI-powered medical voice assistant that enables users to have real-time voice consultations with specialized AI doctors, generate structured consultation reports, and revisit prior sessions through persistent history. The application combines a Next.js and React front end with Python-based AI services, speech-to-text and voice interaction workflows, LLM-driven medical reasoning, and back-end persistence for session management. I focused on the full-stack architecture, AI integration layer, and conversational UX so the product could deliver responsive voice experiences, structured outputs, and scalable doctor-style interactions in a production-oriented web application.

I built a portfolio-grade full-stack SaaS application that converts design system ideas into structured AI-generated diagrams. Users can describe a system in plain text, speak their intent, or provide a GitHub repository URL, and the platform transforms that input into Mermaid-based architecture and component diagrams with conversational refinement. The solution uses a modern Next.js front end and Python and FastAPI AI services with resilient prompt enhancement, validation, retry handling, export support, and version-aware iterations. My work covered the end-to-end product architecture, AI orchestration, UX flows, and error-tolerant delivery needed for a polished and reusable developer tool.

I developed an AI-enhanced note-taking platform using Next.js, React, TypeScript, Tailwind CSS, and a real-time back end powered by Convex. The product supports fast note creation, semantic organization, vector-powered search, and AI-assisted retrieval, so users can manage information through natural language rather than relying solely on manual folders. I integrated the Vercel AI SDK with OpenAI models to improve note generation, summarization, and discovery, while also shaping the front-end architecture, authentication flows, and responsive interface patterns required for a smooth day-to-day productivity experience.

I built a full-stack AI platform that evaluates geographic locations to identify business opportunities, market gaps, and competitive signals. The application integrates Google Maps and Places APIs for live location intelligence, processes the collected context through GPT-based analysis, and generates actionable recommendations and downloadable reports for business decision-making. I worked across the front-end experience, API integration layer, authentication, persistence, and AI analysis workflows to enable users to move from map-based exploration to structured opportunity insights within a single product flow.

I created an AI-enabled nutrition and meal-tracking application that helps users plan meals, monitor habits, and receive more personalized dietary guidance based on their activity data. The product combines a React Native mobile experience with AI-assisted recommendation flows, structured tracking, and a clean UI focused on everyday usability. I contributed to the application architecture, user flows, error handling, and interaction design so the app could support consistent daily engagement while keeping the experience responsive, modern, and easy to extend with future health and recommendation features, which were key to its successful development. Use our enhanced text formatting guidelines

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I built an AI-driven learning and assessment platform that helps educators transform static study materials into adaptive quizzes and personalized practice flows. Teachers can upload PDFs, documents, or raw text, and the system extracts content, applies OCR and NLP-based processing, and generates curated multiple-choice or free-response assessments with configurable rules. I designed the product to support student progress tracking, analytics dashboards, secure sharing, and adaptive learning journeys, combining AI content processing with a full-stack web application experience for both instructors and learners.

I developed a CMS-driven weather platform with a secure BFF architecture, combining a Strapi back end with a Next.js App Router front end and a custom admin dashboard. The system supports draft and publish workflows, role-based access control, ISR-powered public pages, cached data access, and secure weather and geocode proxy APIs backed by HttpOnly JWT authentication. My work covered the content architecture, front-end delivery layer, API security model, and resilience features such as error boundaries and test coverage, producing a scalable MACH-aligned application ready for cloud deployment.

I built a university search and discovery dashboard that helps students evaluate study-abroad options through structured filtering and comparison. The application allows users to explore institutions based on meaningful criteria, quickly surface relevant matches, and browse results through a clean, accessible interface. I focused on the front-end experience, search workflow, and data presentation patterns to turn a simple dataset into a more useful decision-support tool for students researching international education opportunities.