Freelancers using Next.js in GhaziabadFreelancers using Next.js in Ghaziabad
Versatile Fullstack Engineer | Web & Mobile Expert
$50k+
Earned
5x
Hired
5.0
Rating
117
Followers
Versatile Fullstack Engineer | Web & Mobile Expert
Full Stack Developer | MVPs, SaaS & Dashboards for Startups
$10k+
Earned
5x
Hired
4.9
Rating
25
Followers
Full Stack Developer | MVPs, SaaS & Dashboards for Startups
Mobile App Architect • React Native Expert • 50+ App Shipped
$5k+
Earned
1x
Hired
5.0
Rating
18
Followers
Mobile App Architect • React Native Expert • 50+ App Shipped
Cover image for PromptOT – AI Prompts Get
PromptOT – AI Prompts Get Refined, Versioned, Evaluated & Shipped PromptOT is a prompt management platform designed to help AI teams treat production prompts as production code. It lets teams author prompts in structured, typed blocks, version every change with full history and rollback, evaluate versions against saved test cases across multiple models, and deliver the compiled, variable-driven prompt to their application via a single API call or native MCP integration, with no redeploy required. We built a compilation engine solid enough for production use, an AI co-pilot for conversational prompt editing with inline diffs and scoring, and native support for the tools AI teams already use daily - Claude Desktop, Cursor, ChatGPT, Codex CLI, Windsurf, and Zed. Key Features - Typed Prompt Blocks Semantic Versioning with Rollback Evaluations Across Models API & MCP Delivery AI Co-Pilot for Prompt Editing AI teams often struggle with - Prompts scattered across a Google Doc, a Slack thread, someone's Notion, and hard-coded strings in the codebase No version history, no diffs, no way to know which version is actually live No way to evaluate a prompt rewrite before shipping it to production Legal and brand review happening informally in DMs, if at all PromptOT delivers a single source of truth for every production prompt, shipped by API or MCP. It bridges the gap between prompt experimentation and reliable, production-grade delivery, turning prompts from fragile prose into managed, versioned infrastructure.
2
1
179
AI Agent Developer & Engineer | MCP, LLM apps, automation
1x
Hired
5.0
Rating
61
Followers
AI Agent Developer & Engineer | MCP, LLM apps, automation
AI Automation | Full-Stack Dev | Web3 | 8× 🏆 Hackathon
5.0
Rating
29
Followers
AI Automation | Full-Stack Dev | Web3 | 8× 🏆 Hackathon
Full Stack Developer
20
Followers
Full Stack Developer
Cover image for Multi-Vendor E-Commerce Marketplace
Designed and developed
Multi-Vendor E-Commerce Marketplace Designed and developed a scalable multi-vendor e-commerce marketplace connecting customers, sellers, and administrators through a unified platform. Overview A modern marketplace platform built for multiple independent vendors, allowing sellers to manage products, inventory, orders, pricing, and fulfillment, while customers can discover products, compare options, purchase securely, and track their orders. Key Features - Multi-vendor seller registration and onboarding - Seller dashboards with products, inventory, orders, and sales - Advanced product catalog with categories, variants, attributes, and pricing - Powerful search, filtering, sorting, and product discovery - Product details, reviews, ratings, wishlist, and saved items - Shopping cart and secure checkout - Multiple payment methods and automated vendor payouts - Order management and real-time order status - Customer accounts, addresses, order history, and tracking - Vendor storefronts and profiles - Promotions, coupons, discounts, and featured products - Admin dashboard for users, vendors, products, orders, payments, and commissions - Vendor commission and revenue management - Responsive design across desktop, tablet, and mobile - Scalable architecture prepared for large product catalogs and growing traffic UX & Design The interface was designed around a clean, conversion-focused shopping experience inspired by leading marketplaces such as Amazon, eBay, Wayfair, etc. The focus was on intuitive navigation, fast product discovery, clear product information, frictionless checkout, and dedicated experiences for both buyers and sellers. Outcome Delivered a complete marketplace foundation designed to support multiple vendors, thousands of products, secure transactions, automated workflows, and scalable business operations.
0
31
Cover image for AI Resume Screening | Candidate
AI Resume Screening | Candidate Ranking System | AI HR Recruiter | ATS CV/Resume Optimization 𝗢𝘃𝗲𝗿𝘃𝗶𝗲𝘄 Recruiters often spend hours manually reviewing resumes, comparing candidate qualifications, and identifying the best fit for open positions. To address this challenge, I developed an AI-powered Resume Screening and Candidate Ranking Platform that automates candidate evaluation, improves hiring efficiency, and reduces recruitment time. 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲 Traditional recruitment processes involve reviewing hundreds of resumes for a single position. This manual approach is time-consuming, inconsistent, and often results in qualified candidates being overlooked. Recruiters needed a solution capable of quickly analyzing resumes, matching them against job requirements, and generating reliable candidate rankings. 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻 I built an intelligent recruitment platform that leverages Artificial Intelligence and Natural Language Processing (NLP) to automate resume analysis and candidate assessment. 𝗞𝗲𝘆 𝗳𝗲𝗮𝘁𝘂𝗿𝗲𝘀 𝗶𝗻𝗰𝗹𝘂𝗱𝗲: - ATS-compatible resume parsing for PDF and DOCX files - Automated extraction of skills, experience, education, certifications, and contact information - AI candidate matching based on job descriptions - Intelligent candidate scoring and ranking system - Semantic skill matching using NLP techniques - Automated shortlist generation for recruiters - Recruiter dashboard for managing applications and rankings - Bulk resume processing for high-volume recruitment - Interview recommendation system based on candidate fit - Fair and consistent evaluation framework to reduce manual bias 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 𝗣𝗿𝗼𝗰𝗲𝘀𝘀 The platform was designed with scalability and accuracy in mind. The workflow begins by parsing uploaded resumes and extracting structured candidate data. AI models then compare candidate profiles against job requirements, analyzing technical skills, years of experience, educational background, and industry relevance. A ranking engine generates compatibility scores and presents candidates in order of suitability. Recruiters can review detailed scoring insights, compare applicants, and make faster hiring decisions. 𝗥𝗲𝘀𝘂𝗹𝘁𝘀 The solution significantly improved recruitment efficiency and candidate discovery. 𝗢𝘂𝘁𝗰𝗼𝗺𝗲𝘀 > Reduced manual resume screening time by up to 80% > Accelerated candidate shortlisting process > Improved recruiter productivity and hiring speed > Increased consistency in candidate evaluation > Enabled processing of hundreds of resumes within minutes > Enhanced talent identification through AI-driven matching 𝗖𝗼𝗻𝗰𝗹𝘂𝘀𝗶𝗼𝗻 This AI recruitment platform transforms traditional hiring workflows by automating resume screening, ranking candidates intelligently, and helping recruiters identify top talent faster, more accurately, and at scale.
1
236
Full Stack Engineer building Fast Websites and Web Apps
27
Followers
Full Stack Engineer building Fast Websites and Web Apps
Shopify & Next.js Expert | Custom Stores That Stand Out
7
Followers
Shopify & Next.js Expert | Custom Stores That Stand Out