Web Development Projects in FaisalabadWeb Development Projects in FaisalabadSoulDeeds — Full-Stack Community & Connection Platform
Project Overview
SoulDeeds is a high-performance, full-stack web application designed to facilitate meaningful and purposeful connections within a community. As a Lead Developer, I architected and built the entire system focusing on scalability, real-time interactions, and a premium user experience.
The Challenge
The goal was to create a secure, high-traffic platform that balances a modern UI with complex backend logic for user verification and community matchmaking.
Core Contributions & Features
Full-Stack Architecture: Developed a robust end-to-end system using Next.js and React for the frontend, and Node.js for the backend.
Database Management: Integrated MongoDB to handle complex user data, relationships, and dynamic content efficiently.
RESTful API Development: Built secure and scalable REST APIs to manage authentication, profile verification, and data flow between the frontend and server.
UI/UX Specialist Approach: Implemented a sophisticated, responsive design using CSS3 and modern styling libraries, ensuring a seamless experience across all devices.
Community Features: Engineered logic for verified profiles and "halal connections," prioritizing user safety and community integrity.
Tech Stack
Frontend: Next.js, React.js.
Backend: Node.js, Express.
Database: MongoDB.
APIs: REST API Architecture.
Styling: Advanced CSS3, Responsive Design. App Name: GigPulse
Category: 📊 Dashboard + 🤝 Social/Community
What it does:
GigPulse is a personal freelance project tracker built for independent professionals who juggle multiple platforms. Freelancers can log their projects, track earnings per platform, monitor project status, and attach video demos of their work all in one private dashboard. The community benchmarking layer lets users see anonymized stats from other freelancers in their niche, so you always know how you stack up.
How I built on top of the AI-generated base:
Bubble AI generated the core dashboard structure and data architecture. From there, I manually engineered the video upload and playback system per project, built privacy-filtered data workflows so each user only sees their own data, added platform-specific earnings tracking with status badges, and designed a clean dark UI with collapsible video players. The AI gave me the skeleton, I built the muscles.
This is the Bubble AI-generated base after my initial prompt 'Build a freelance analytics dashboard app called "GigPulse" where
freelancers can track their gigs, proposals sent, earnings per platform,
client response rates, and monthly revenue goals. Include a community
benchmarking section where users can see anonymized stats from other
freelancers in their niche. Add user authentication, a personal stats
dashboard with charts, a goal-setting tracker, and a community feed
where freelancers share weekly wins.'
Everything you see in the final build beyond this point was manually engineered. Keyword Finder, AI SEO Keyword Research & SERP Intelligence SaaS
Built a distributed SEO research platform that expands a single seed keyword into thousands of opportunities combining Google Ads volume data, live SERP analysis, NLP competitor scoring, domain authority metrics, and AI content brief generation into one unified workflow with no CSV exports or tool-switching.
SEO agencies were stitching together four or five separate tools a keyword research tool, a SERP analyser, a domain authority checker, an NLP scorer, and a rank tracker and manually reconciling their exports in spreadsheets. Scaling that workflow across multiple clients and thousands of keywords every month was unsustainable.
Keyword Finder is built on Django 5, FastAPI, Flask microservices, React 18, and GPT-4o. The platform supports 4 keyword generation modes — Seed, URL, Competitor, and Bulk. In Seed mode it builds prefix, suffix, and alpha combination lists, fires them to Google Autocomplete in parallel with rotating proxies, then runs a second deep expansion round before fetching volume, CPC, and competition data from the Google Ads API via OAuth2. SERP analysis jobs are distributed across a dedicated Flask scraping microservice fleet with round-robin load balancing and a four-tier fallback chain direct, Bright Data, scraping.narf.ai (http://scraping.narf.ai), and CrawlBase — ensuring near-100% page retrieval success regardless of target site protection. Each competitor URL is processed through a full NLP pipeline using YAKE and NLTK, with domain authority pulled from Moz and Majestic via DomDetailer and cached locally to avoid redundant API calls.
The Ranking Recipe lets agencies define custom Easy, Medium, Hard, and Easiest thresholds across 12 metrics turning keyword prioritisation from guesswork into a data-driven decision. AI content briefs are generated using GPT-4o and Cohere with full keyword context, cutting brief writing time from hours to minutes. Real-time job progress is delivered via Django Channels WebSockets, with Celery and Redis managing the async scraping queue. Supports 200+ Google country domains for multi-market research.
Tech Stack: Django · FastAPI · Flask · React · GPT-4o · LangChain · Celery · Redis · PostgreSQL · Google Ads API · Bright Data · YAKE · NLTK · Moz · Majestic · Material UI · Redux 
