Full Breakdown
AI-Driven Replication of India’s Traditional Textiles: Opportunities, Ownership and Legal Gaps
By Drooid · · How we work
Core Event – AI Systems Generate Traditional Motifs at Scale
Assistant professor Bitupan Deka of MIT University in Shillong has built an AI-driven design system that can create unlimited new patterns for the “gamusa” scarf and other regional fabrics. The system is being patented for commercial licensing. At the India AI Impact Summit in New Delhi, Tata Consultancy Services (TCS) demonstrated “Bridgital Loom,” an AI tool that converts designs into loom-ready instructions, with a pilot running in Kanchipuram, Tamil Nadu.
Background & Context – Decades of Digitising Textile Heritage
India’s textile memory has been documented through the Botanical Survey of India, the Bharatiya Vastra Shilpa Kosh portal, and high-resolution datasets such as the Rekh Sanganeri collection. These archives now supply raw data for generative AI models.
Data & Statistics
- Weavers in Sualkuchi (Assam) receive a one-time payment of roughly 2,000 rupees per design.
- 15 years is the typical apprenticeship period to master a handloom craft, according to TCS’s AI-strategy head.
- The AI-handloom research centre at the Centre of Excellence for Handloom Technology (IIT New Delhi) was funded with $1.4 million.
Official Statements & Responses
Deka says his tool is meant to assist, not replace, traditional designers. TCS asserts that Bridgital Loom helps weavers execute complex Banarasi and Kanchipuram patterns faster and with fewer errors.
The Department for Promotion of Industry and Internal Trade issued a “blanket licence” in December 2025, allowing AI developers to train on lawfully obtained copyrighted material; royalties would be set by the state once commercialised.
Muthulakshmi Nellaiappan, head of AI strategy for Bridgital Loom, noted that the system works with non-electronic handlooms and can accelerate a novice’s path to mastery.
On-the-Ground Reports
While shopping in Shillong, Deka observed many shops sold the same handful of scarf patterns, prompting his investigation into the one-time-fee model that limits design diversity.
Ananthalakshmi Vadivel, a third-generation weaver from Kanchipuram, acknowledges that AI-enabled looms can produce cheaper sarees that compete in the market, but she insists authentic hand-woven Kanchipuram pieces will retain a distinct market among discerning buyers.
Conflicting Reports & Gaps
India’s IP framework assumes a traceable author, yet traditional motifs are communal property. No clear legal precedent exists to determine whether royalties should go to the artisan, the photographer, the dataset compiler, or the AI developer, leaving artisans vulnerable to exclusion from future revenue streams.
Verbatim Quotes
- “My work isn’t meant to replace the traditional designers. I hope, instead, that it will become a tool in their hands to create new and modern motifs more easily, so the consumers can have variety,” — Bitupan Deka
- “You cannot separate the names from the community. Call your mass-produced work digital prints and leave the traditional names to the original artisans,” — Dinesh Chhipa
What’s Next – Government Initiatives and Industry Pilots
The AI-handloom research department plans to register thousands of weavers, equip handlooms with sensors that digitise weave patterns, and issue QR-coded tags to trace provenance. Maharashtra’s Vingatha system already authenticates Paithani and Karvat Kathi sarees at the state level. These measures aim to increase visibility for artisans as AI tools continue to enable mass production of traditional designs.