Freelancers using MongoDB in Agra
Freelancers using MongoDB in Agra
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Aryan Raghav
Agra, India
AI Engineer building scalable AI & SaaS products
New to Contra
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AI Engineer building scalable AI & SaaS products
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Developed GoNomad, a full-stack MERN car rental platform that connects travelers with trusted vehicle owners through a seamless booking experience. Built responsive user interfaces with React, implemented secure JWT-based authentication and role-based access control, and designed a conflict-free booking system using date-overlap validation. Integrated AI-powered vehicle description generation with the Groq API to streamline listings and optimized image delivery using ImageKit CDN for faster load times. The platform emphasizes performance, security, scalability, and an intuitive user experience across devices.
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The definitive, interview-focused open-source curriculum for modern AI Engineering. Bridging the critical gap between Classical Machine Learning and Generative Foundation Models.
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37
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Resolving Indic Idioms for Better Machine Translation
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5
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Built Solvi, an AI-powered interview preparation platform for mastering the NeetCode 150. Features personalized study plans with Google Gemini, spaced repetition scheduling, progress tracking, analytics, and an interactive DSA cheatsheet. Developed using Next.js 16, React 19, Tailwind CSS, Prisma, SQLite, and TanStack React Query with secure client-side API key handling
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40
MongoDB
(1)
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RIPSUDHAN MISHRA
Agra, India
Web Developer | UI/UX designer | Data Analyst
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Web Developer | UI/UX designer | Data Analyst
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A MERN video calling and chat application.
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168
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Built an AI concierge for a luxury fashion brand ๐ค Wanted to push past a basic FAQ bot, so I built "รlise" โ a fully branded AI concierge for a fictional boutique fashion label, Maison รlise. ๐น Greets visitors by name-dropping exactly what she can help with, hours, shipping, returns, styling appointments ๐น Quick-reply buttons for the most common questions, so visitors barely have to type ๐น Real, specific answers โ not vague filler. Ask about shipping and she'll tell you the actual cost, free-shipping threshold, and same-day cutoff time ๐น Fully on-brand: the concierge panel matches the site's warm, editorial aesthetic instead of feeling like a bolted-on support widget ๐น Connected admin panel to track how the concierge is being used The goal wasn't "add a chatbot" โ it was making the AI feel like an actual extension of the brand's in-store experience, the way a real concierge would greet you walking into a boutique. Built entirely in Base44 ๐ https://elise-chat-flow.base44.app/
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Small Batch Coffee Roaster Storefront
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61
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Instant Quote Widget โ Embeddable Lead Generation Tool
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5
MongoDB
(1)
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Sachin Shrivastav
Agra, India
Full-Stack SaaS Developer | Node.js, TypeScript, React
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Full-Stack SaaS Developer | Node.js, TypeScript, React
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THE JOURNAL- Next.js Blog Application with TailwindCSS
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I've contributed as a lead engineer to a multi-tenant HR SaaS platform, owning major backend architecture and full-stack feature delivery. I designed and built a workflow and approval engine supporting parallel execution, quorum-based approvals, delegation, SLA-based escalation, decision tables, and sub-workflows. I also built its visual workflow designer, template/document generation, forms, search, authorization, integrations, and observability capabilities. The platform uses TypeScript, Cloudflare Workers, Hono, PostgreSQL, Drizzle ORM, React, TanStack, Cerbos, and OpenTelemetry.
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Built and maintained major parts of a production real estate technology platform covering property management, leads, referrals, tours, analytics, reporting, and third-party integrations. I owned substantial backend and frontend functionality using NestJS, PostgreSQL, Prisma, Redis, React, Redux Toolkit, AWS, and Socket.io (http://Socket.io). My work included high-volume analytics, database optimization, reporting pipelines, timezone-aware scheduling, complex forms, multi-tenant functionality, and integrations with external real estate and productivity platforms.
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Built a distributed data ingestion system for collecting listing, lead, and analytics data from multiple real estate data sources. The system used Python, FastAPI, Celery, Redis, Selenium Grid, and Docker to coordinate authenticated scraping across concurrent workers. I designed shared session management using Redis locks and pub/sub, parallelized scraping workloads with Celery, and implemented missing-page reconciliation to improve reliability. The production pipeline was designed to process large ingestion workloads reliably without manual intervention.
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30
MongoDB
(1)
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Saran Sinha
Agra, India
Frontend focused full-stack developer
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Frontend focused full-stack developer
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FlockUp
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7
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ConnectifAI
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9
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EasyRooms
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9
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MongoDB
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Prabhav Chandra
Agra, India
Fullstack Developer | Atlassian & Amazon Intern
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Fullstack Developer | Atlassian & Amazon Intern
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Alumni Portal
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5
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Website (Dgjobmasters)
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10
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Armkendra web app
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7
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MongoDB
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