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This is the repo for prototype of the Build for Bharat hackathon, by team Progmatic , MAIT

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CatalogCraft

Catalogue Digitization by Team Progmatic

Overview

This is the repository for the prototype of the Build for Bharat hackathon. The aim of this project is to digitize Indian catalogues and make them searchable on a platform. This repository contains the source code for a webapp.

Hosted Link Admin Dashboard

Table of Contents

Installation

Follow these steps to set up the development environment:

  1. Clone the repository:

    git clone https://github.com/exploring-solver/CatalogCraft.git
    cd frontend
  2. Install Dependencies:

    npm i
  3. Start the development server:

    npm run dev

    The application should now be running at http://localhost:5173

Problem

The challenge is to develop innovative solutions that leverage cutting-edge technologies to seamlessly digitalize and enhance product catalogs, offering a user-friendly experience for sellers and seller apps. Consider a sample catalog with at least 1000 SKUs, with attributes such as SKU id, product name, description, price, image, inventory, colour, size, brand, etc. This catalog is to be digitized using a combination of intuitive interfaces such as text / voice / image input, with text & voice input using any of the Indic languages. In some cases, a combination of these interfaces are required to digitize an SKU e.g. scan image which pre-fills the product name from the repository, with the remaining attributes filled using text or voice input.

Solution

  • Process Inefficiency and Time inefficient
  • Resource Redundancy
  • Catalog integrity issues, Image Quality and accuracy
  • Lack of Standardization, Consistency Issues
  • Multiple steps and clicks involved
  • UX friction, CX pain points

Deliverables

  • Barcode Scanning
  • Voice Input
  • Vector Image search
  • Mapping to master catalogue
  • Download reported analytics
  • Adheres to taxonomy
  • Standardized and non-standardized product support
  • Catalog Templates
  • YOLO Model to detect items and fill their catalogue
  • Seamless Multilingual Support Integration
  • Robust chatbot which supports all major languages
  • Dual backend and database integration options (Django and Nodejs)
  • Bulk data addition and instant catalog creation
  • Auto Filling Maximum Data

Technology

React Material-UI TailwindCSS Django PostgreSQL Node.js MongoDB Kotlin

Team

  1. Aman Sharma
  2. Ravi K Banchhiwal
  3. Ishaan Minocha
  4. Shivam Kumar Jha

Thank You!

Please star the repository :)