Incardible is an e-commerce platform I developed that combines physical greeting cards with personalized augmented reality experiences. Users can browse card designs, customize their greetings, and upload digital content, making each card a more personal and memorable gift.
🔹 Key Highlights:
Personalized Card Creation – A customization flow that helps users create greetings tailored to their recipient.
Augmented Reality Content – Digital content uploads connect physical cards with an interactive experience.
Card Design Previews – Users can preview the front and inside of available cards before choosing a design.
Online Shopping Experience – Card browsing, price sorting, and purchasing features bring discovery and ordering into one platform.
Modern Web Development – Built with Next.js and integrated backend APIs to support card browsing, customization, and commerce workflows.
🌟 Impact:
Incardible brings a creative digital layer to traditional greeting cards, helping customers turn a simple gift into a personalized experience. The platform connects design selection, customization, and online purchasing in one convenient journey.
Website: https://incardible.com.au/
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Shop Smarter with QUFFAH 🛍️
Your modern e-commerce store built by Repla Technologies.
Fast, secure, and seamless shopping designed to elevate your online experience.
Discover a store that brings quality, convenience, and style together.
Get in touch: info@replatechnologies.co.uk
(mailto:info@replatechnologies.co.uk)visit: www.replatechnologies.com
(https://www.replatechnologies.com)
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Designed and built a premium e-commerce experience focused on visual storytelling and conversion.
Featuring immersive product showcases, category browsing, product details, interactive shopping bag, quantity management, and a streamlined checkout experience.
Built to make the brand feel premium while keeping the shopping journey simple and intuitive.
Have a brand that needs a high-end digital experience? Let’s work together.
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Stock Market Analytics Platform
My role. Frontend Engineer
Developed frontend using Next, Redux, TypeScript ,Material UI, Storybook and Tailwind CSS.
integrated UI/UX design graphs such as bar and line graphs for visual representation of data.
Successfully implemented stock filtering functionality on the automated scraped data.
converted the project from JavaScript to TypeScript for enhanced maintainability.
Utilized Storybook for isolated UI component visualization.
Developed test suites, validating the functionality and behavior of components.
Worked with firebase authentication and cloud store.
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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
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