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Aptly - AI-Powered Job Matching & Resume ATS Platform
Architected and developed a full-stack SaaS platform (32,000+ LOC) that revolutionizes recruitment with semantic resume parsing, ATS scoring, and intelligent candidate matching.
Key Highlights:
• Automated resume ingestion & text extraction using intelligent parsing algorithms
• Dynamic job-to-resume matching engine with skill-gap scoring and analytics
• Recruiter & applicant dashboards featuring real-time pipeline tracking and interview scheduling
• Engineered with React, Node.js, Express, MongoDB, JWT auth, and modular MVC architecture
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
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🚀 Introducing WanderLust — My Full-Stack Web Development Project
I built WanderLust, a full-stack booking web application using Node.js, Express.js, MongoDB, and EJS.
✨ Key features:
User authentication and authorization
Create, edit, and manage property listings
Reviews and booking functionality
Image uploads using Cloudinary
Interactive maps with Mapbox
Search and category filters
🛠️ Tech Stack: JavaScript, Node.js, Express.js, MongoDB, Mongoose, EJS, Passport.js, Cloudinary, and Mapbox.
This project helped me strengthen my backend development, database integration, authentication, and deployment skills.
I'm a junior full-stack developer interested in building useful web applications and collaborating on real-world projects.
🔗 Live Demo: https://wanderlust-tphz.onrender.com
💻 GitHub: https://github.com/Aabi-dev10/WanderLust
#FullStackDevelopment #MERNStack #JavaScript #WebDevelopment #NodeJS
did you build the reviews and booking flow first?
𝐀𝐈 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 & 𝐃𝐚𝐭𝐚 𝐐𝐮𝐞𝐫𝐲 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦
I built an AI-powered research intelligence platform that helps analysts and business teams query complex datasets through a single conversational interface.
𝐓𝐡𝐞 𝐏𝐫𝐨𝐛𝐥𝐞𝐦
Research teams often work across disconnected databases, reports, spreadsheets, dashboards, and documents. This slows analysis, makes cross-source searching difficult, and can reduce trust in AI-generated answers.
𝐓𝐡𝐞 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧
The platform combines RAG, AI agents, natural-language-to-SQL, structured and unstructured retrieval, source attribution, confidence scoring, and evaluation pipelines.
Users can ask a business question in natural language, and the system decides whether to search documents, query databases, run SQL, or combine multiple sources before returning an evidence-backed answer.
𝐀𝐜𝐜𝐮𝐫𝐚𝐜𝐲 & 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐄𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞
The system evaluates answer correctness, retrieval quality, SQL accuracy, source relevance, hallucination risk, and response performance. Low-confidence results are captured for review and continuous improvement.
The frontend is built with React + TypeScript and includes AI chat, dataset exploration, source references, analytics, evaluation dashboards, and real-time updates.
𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐕𝐚𝐥𝐮𝐞
The platform helps teams analyze data faster, reduce manual SQL work, improve trust in AI outputs, and uncover insights across multiple data sources.
𝐓𝐞𝐜𝐡 𝐒𝐭𝐚𝐜𝐤: 𝐑𝐞𝐚𝐜𝐭 • 𝐓𝐲𝐩𝐞𝐒𝐜𝐫𝐢𝐩𝐭 • 𝐏𝐲𝐭𝐡𝐨𝐧 • 𝐏𝐨𝐬𝐭𝐠𝐫𝐞𝐒𝐐𝐋 • 𝐑𝐀𝐆 • 𝐕𝐞𝐜𝐭𝐨𝐫 𝐒𝐞𝐚𝐫𝐜𝐡 • 𝐋𝐋𝐌 𝐀𝐠𝐞𝐧𝐭𝐬 • 𝐒𝐐𝐋 • 𝐀𝐏𝐈𝐬 • 𝐄𝐯𝐚𝐥 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬
Full-Stack Platform Built for Orqelix Services
Modern Frontend: Dynamic, responsive UI crafted with React, HTML5, and CSS3.
Enterprise Backend: High-performance architecture powered by Java and Node.js.
Core Focus: Seamlessly scaling AI/ML workflows, automation, and software engineering.
Take a look into Live website on google - https://www.orqelix.in
