AI Enhanced Handloom Platform For Direct Weaver to Customer Sales

In order to preserve legacy and the economic survival of indigenous weavers, handloom textile items are crucial to the local population’s financial and cultural environment. Therefore, precise and effective techniques for authenticating against imitation powerloom textiles are required. Using a deep metric learning strategy, this research introduces a novel method for the automatic identification of handloom textiles. Working with native weavers in Assam, northern India, a labelled handloom fabric dataset of $\mathbf{2 5, 1 6 6}$ photos was produced by gathering samples of six distinct types of handloom textiles. The handloom industry faces challenges like limited market access and middlemen exploitation. This paper presents an AIenhanced e-commerce platform that enables direct weaver-to-customer sales through real-time chat, live product demos, and AI-driven recommendations using NLP and LSTM. The system ensures seamless product management, secure transactions, and personalized shopping experiences, empowering artisans while enhancing market accessibility.