skinsforskin is a React-based web app that transforms skincare with personalized suggestions via OpenAI API and ingredient analysis for products.
Auto encoders based recommendation system
Open-source framework for cold-start recommendations and lazy knowledge graph construction from product catalogs
This repository includes a web application that is connected to a product recommendation system developed with the comprehensive Amazon Review Data (2018) dataset, consisting of nearly 233.1 million records and occupying approximately 128 gigabytes (GB) of data storage, using MongoDB, PySpark, and Apache Kafka.
Smart pharmacy assistant for ViaPharma customers. Provides personalized OTC product recommendations based on symptoms using medical AI and safety-first approach.
A dummy E-Commerce website with 3 recommendation systems, that recommends products based on customer reviews of products from a public dataset.
Compare live prices across Amazon, Flipkart, Meesho, Myntra, and JioMart with transparent weighted buying recommendations.
Product recommendation components designed by a language model and rendered as React Server Components. The model returns a validated specification, never markup, so it cannot invent a price, a rating or a stock level.
Laravel post-purchase email demo: Stripe checkout webhook triggers an order confirmation that includes AI-picked product recommendations from a seeded catalog, delivered via Mailtrap with sandbox toggle.
This project focuses on exploring product recommendations within the realm of luxury fashion resale. It serves as a companion to my thesis of the MSc Marketing Analytics program at TiU.
Emporiqa Chat Assistant module for Shopware
Emporiqa Chat Assistant module for PrestaShop
Relewise demo shop featuring Search & Recommendations built on top of the Relewise JavaScript SDK using Vue
A drop-in, grounded AI shopping assistant that recommends real products from your catalogue. Bring any OpenAI, Anthropic, Gemini, or Groq key.
Collect Amazon Rufus recommendations and product-aware answers through the Scrapeless Scraping API.
Beauty product recommendation scout with live research and email delivery.
Conversational AI shopping assistant for e-commerce — product discovery, recommendations, and order support powered by Azure OpenAI and Semantic Kernel.
Toppp, an AI-assisted shopping answer engine for trusted product recommendations.
ML-powered product recommendation system that analyzes guest reviews using sentiment analysis (DistilBERT) to surface bestselling products by category and generate actionable insights for underperforming ones. Built for Target India's application challenge.
AI-powered product bundling and recommendations engine. Create complementary bundles to boost average order value.
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