The Indian Handmade Rug & Carpet Industry at a Crossroad – Can Tech play a role?

The Indian handmade rug and carpet industry, which accounts for 40% of the global floor covering trade, now faces significant challenges. In FY 22, exports reached $2.23 billion but dropped sharply to $1.83 billion in FY 23 - a concerning 18% decline. While a slight recovery to $1.87 billion in FY 24 offers some hope, the industry must address pressing issues to regain its footing. The three major carpet clusters - Bhadohi-Mirzapur-Gopiganj in Uttar Pradesh, Panipat in Haryana, and Kashmir—are feeling the heat.?

What is keeping the Industry awake at night?

a. Shifting Consumer Preferences and Supply Chain Disruptions

The COVID-19 pandemic significantly altered consumer behavior, with customers increasingly seeking affordable, low-maintenance products. The handmade industry faces pressure from both ends—cheaper machine-made alternatives from countries like Turkey and better-designed, machine-made products from the US and EU. This shift, coupled with supply chain disruptions triggered by the pandemic, is straining traditional manufacturers.

b. Skilled Labor Shortage and Industry Stagnation

A critical concern is the migration of skilled artisans to other professions, compounded by a lack of new talent entering the field. The intricate craftsmanship required for handmade carpets is at risk as weavers, discouraged by diminishing returns, seek employment elsewhere, including under the MGNREGS scheme.

Talent scarcity, combined with geopolitical uncertainties, economic challenges and policy stagnation, threatens the industry’s survival. Stakeholders have witnessed the decline or disappearance of once-thriving segments like Dhurries and coir mats, signaling a potential crisis for the handmade sector.

Does Technology have an answer?

As a technology enthusiast and someone who spent around 10 years in the handmade rugs industry, I believe the industry's future lies in balancing transformative technologies with its rich heritage of craftsmanship. I am optimistic!!

My intent here is to crystal gaze, to explore the potential of emerging technologies in a three-part series starting with its impact on design, followed by production and customer experience. In the fourth section I will outline my thoughts on how this can be executed at the ground level. Given the evolving nature of these technologies and the prohibitive costs for individual companies, collaboration becomes crucial. This is an Industry-wide challenge and demands active participation from all stakeholders including the Carpet Export Promotion Council (CEPC) and the Government, to rejuvenate the Industry’s momentum

Design: The Brain of Every Carpet

At the core of every exceptional carpet lies its design. It’s the unique signature of the designer that elevates a piece from good to great!! Having collaborated with some of the best design talents from NIFTs and NID, I’ve observed that most designers—like other right-brained creators—prefer to immerse themselves in creation rather than in mundane tasks like note-taking or searching for information. Future technologies must empower designers to focus more on their art, reducing operational hurdles and enabling them to bring their creative visions to life with greater ease

Carpet and textile designers typically focus on three key outputs:

1. Creating collections for specific seasonal trade fairs or showroom resets

2. Client-specific projects, whether the brief is generic or highly detailed

3. Customization—re-coloring, re-imagining, or resizing designs that have already caught customers’ eyes

Currently, while carpet design software like NedGraphics’ Texcelle, Galaincha, and Naqash (for hand-knotted carpets) are available many designers remain more comfortable triggering their ideation process with generic tools like CorelDRAW and Photoshop rather than specialized carpet design software.

I see the following tech interventions alter the life of a Rug Designer:

a. Trends Forecasting, Predictive Analytics, and Mood Board Generation

Pre-creation, designers spend significant time scouring trends and forecasts to prepare the next season’s collection. References from forecasting publications, subscriptions of color trends, surrogates for forecasting home décor trends are collated, synthesized and transformed into a mood board, marking the beginning of the creation process?

Transformative tech can play a pivotal role here. AI tools that combine visual recognition technology with social media and search data, such as Trendalytics, Next Atlas, and Mobifish AI, provide valuable insights into trends. Companies like Heuritech offer real-time social media analysis involving celebrities & influencers, capturing emerging trends as they happen and a capability to forecast trends 1 year out —an essential differentiator from traditional long-term published trends. Luxury brands like Chanel and Dior rely on these analytics. An Indian start-up Sylumia, founded by my ex-colleagues at Reliance Retail, focuses on the mid-market and retail segments within the fashion industry

Designers can use these trend predictions as inputs to tools like Décor AI and Finch to generate mood boards reflecting current styles. Once the mood board is arrived at, the right side of the brain takes over?

While these models are still maturing, with broader training data sets and sharper focus on segments like rugs/carpets and home furnishings, they are poised to become essential tools going forward?

b. Digital Library - AI-Powered DAM with NLQ

A significant portion of a designer’s time is spent searching for reference designs created within the organization. This process can be challenging, especially if the Knowledge was created by someone no longer with the company. An AI-powered Digital Asset Management (DAM) system, enabled by Natural Language Querying (NLQ) ?could be the solution. In fact, this should be a minimum requirement for any organization dealing with vast volumes in a design library

When we attempted to digitize the knowledge of my former company in 2015, we struggled with uniform tagging terminology and retrieval methodology. Keyword meta-tagging was the only technology available at the time, and had to be done manually

Today, advanced computer vision/visual Recognition tools like Google Cloud Vision or Microsoft Azure Cognitive Services can analyze and categorize images automatically, allowing retrieval based on visual content rather than manual tagging. Deploying Retrieval Augmented Generation (RAG) techniques with a feedback mechanism, can enhance retrieval accuracy, eliminate the need for expensive continuous retraining of LLM while keeping it contextual and current at all times. Retrieval happens in a matter of seconds and the possibility of refining the search with contextual follow-up query makes it versatile

Once fully equipped, a designer could query the system to “Show me the designs presented to customer X in Autumn/Winter 2014” or “Show me the collection displayed at Domotex Hannover in 2016.” ?

c. Iterations, Variations, and Ensuring Originality

After landing on a design, the process of exploring variations begins. Currently, this often involves time-consuming rework of certain elements. AI tools like DALL-E 2 and MidJourney can generate multiple variations of a rug within seconds using natural language prompts, sparing designers from rework. For example, they could prompt ?“Give me pastel color variations of this design, replacing the center with different geometric patterns, without changing the border,” and the results would be instantly available for evaluation

As designers produce new iterations, ensuring the originality of their work becomes paramount. In an industry where plagiarism can have significant repercussions, AI-powered image similarity tools like Clarifai, Amazon Rekognition, and Google Cloud Vision AI can help designers verify that their designs are original creations and do not infringe on existing copyrights. This layer of protection not only fosters creativity but also builds confidence in the uniqueness of their work.

d. Contextual AI and the Future of Design – an all-in-one “RugDesignGPT”

As the design process becomes increasingly complex, the need for intelligent assistance grows. Imagine a specialized AI chatbot, much like FinanceGPT or ArchitectGPT, specifically for carpet designers – “RugDesignGPT” tailored to understand the unique challenges of rug design, offering real-time suggestions, generating variations, and even checking for originality on the fly!! This layer of protection not only fosters creativity but also builds confidence in the uniqueness of their work.

The integration of emerging technologies in the design process is more than just about efficiency; it’s about freeing designers from repetitive tasks, enabling them to focus on their core strength—creating. By embracing these technological advancements, the rug design industry can unlock new levels of creativity and innovation, helping Indian handmade rugs regain their past glory