Manasvi Joshi
Full Stack & AI Developer | React, Next.js, Django, FastAPI,
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I developed a modern CRM platform that helps businesses manage leads efficiently through a centralized dashboard. The application enables users to organize their sales pipeline, upload lead data in bulk, and quickly search, filter, and manage customer information.
I built responsive and reusable user interfaces using Next.js, React, and Tailwind CSS, with a strong focus on performance and user experience. The platform leverages Server-Side Rendering (SSR) for improved SEO and faster page loads, while code-splitting and lazy loading reduce the initial JavaScript bundle for a smoother experience.
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Role: Backend Developer (Node.js, Express.js, MongoDB, REST APIs)
ScrapBag is a startup that enables users to sell scrap online through a seamless pickup and payment experience. I was responsible for developing the backend services that powered the customer platform as well as the internal fleet management system.
For the customer application, I built scalable REST APIs for user authentication, scrap pickup requests, order management, and wallet transactions. When a user scheduled a scrap pickup, the system automatically created an order and assigned it to the operations workflow.
I also developed the backend for the fleet management platform used by drivers and field executives. Each driver was associated with a vehicle and could view assigned pickup requests, navigate their collection route, update pickup status, and mark orders as completed in real time.
Once a pickup was successfully completed, the backend calculated the scrap value, updated the order status, and automatically credited the customer's account with the corresponding amount. This ensured a smooth end-to-end workflow from booking a pickup to receiving payment.
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Advanced AI-powered LinkedIn post generation platform that creates engaging, personalized, and high-quality LinkedIn content using an agentic AI workflow. Unlike traditional single-prompt AI tools, this application uses a multi-step reasoning pipeline where the AI plans, researches, brainstorms, generates, validates, and enhances content before producing the final output.
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Built an AI-powered orthopedic healthcare assistant that helps patients describe symptoms, receive general orthopedic guidance, and book appointments through a natural conversational interface. The application combines a Next.js frontend with a FastAPI backend, AI-powered chat, streaming responses, RAG-ready architecture, and appointment scheduling integration. Designed with healthcare safety in mind, it includes structured patient intake, emergency symptom detection, and a scalable architecture that can be extended to WhatsApp, clinic CRMs, and other healthcare platforms.
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