Focal Interest
Focal Interest
AI Summary of Peer-Reviewed Research

This page presents an AI-generated summary of a published research paper. The original authors did not write or review this article. [See full disclosure ↓]

Publishing process signals: STANDARD — reflects the venue and review process. — venue and review process.

AI jewelry platform enabled custom design, chat, and live pricing

A black jewelry display box with a glass lid containing an organized collection of gold and silver rings and bracelets, photographed indoors with natural lighting against a white background.
Research area:World Wide WebArtificial IntelligenceArtificial Intelligence Applications

What the study found

The paper reports that an AI-integrated full-stack web application was designed, implemented, and evaluated for a heritage jewelry retailer. The system combines custom jewelry visualization, a conversational chatbot, live gold and silver prices, and supporting retail features in one platform.

Why the authors say this matters

The authors conclude that the system helps bridge the gap between heritage craftsmanship and modern digital retail. The study suggests it may help democratize access to AI-driven jewelry design for small and medium-sized jewelry enterprises.

What the researchers tested

The researchers built a three-tier web application with a React-TypeScript single-page frontend, an Express.js REST API backend, and MongoDB for storage. They added an AI-powered Design Studio using the Gemma 3 large language model through the Bytez inference API, a chatbot named "Amar," real-time commodity price feeds from the Amar Bullion broadcast streaming API, Google Sheets-based repair tracking, JWT-based multi-role authentication, and a product catalog with dynamic category filtering.

What worked and what didn't

The evaluation found sub-second API response latencies for rate fetching. It also reports seamless AI design generation within acceptable timeframes and a functioning repair workflow from submission through status tracking.

What to keep in mind

The abstract does not provide detailed quantitative evaluation metrics beyond the latency statement. It also does not describe comparative testing, user-study results, or limitations of the system in the available summary.

Key points

  • The paper describes an AI-integrated e-commerce platform built for a heritage jewelry retailer.
  • The system includes an AI design studio, a conversational chatbot, and real-time gold and silver prices.
  • The platform uses React-TypeScript, Express.js, and MongoDB in a three-tier architecture.
  • The evaluation reports sub-second response times for rate fetching and working repair tracking.
  • The authors say the system may help bring AI-driven jewelry design to smaller jewelry businesses.

Disclosure

Research title:
AI jewelry platform enabled custom design, chat, and live pricing
Authors:
Sahil Jagtap, Harsh Mali, Arsh Naikawadi, Aryan Kadam, Om Salunkhe -Patil
Publication date:
2026-02-24
DOI:
10.55041/ijsrem56866
OpenAlex record:
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AI provenance: This post was generated by OpenAI. The original authors did not write or review this post.

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