Page 505 - AI for Good Innovate for Impact

AI for Good Innovate for Impact

Further, AI-powered demand forecasting models will analyze trends and consumer behavior to
inform what should be designed or produced, minimizing waste and aligning supply with actual
demand. This also empowers traditional weavers by digitizing and adapting their patterns for
wider markets. 4.5: Manufacturing

Users will interact with the system through multiple interfaces: Mobile apps (upload photos or
avatars), In-store kiosks (try-ons in retail or artisan fairs), and Designer consoles (for sketch or
text-based garment design). The result is a highly personalized, trust-driven, and sustainable
ecosystem for Indian fashion.

Problem it Aims to Solve

High Return Rates: Inaccurate sizing and fit perception in online shopping contribute to returns,
increasing waste and logistics costs.

Overproduction & Waste: Uncertainty in consumer demand leads to excessive production,
harming sustainability.

Trust Gap in Virtual Try-On: Users may not trust the virtual version of garments to match their
physical fit and feel.

Limited Access to Traditional Fashion: Local artisans and weavers struggle to reach a digital
audience, limiting their market opportunities.

Consumer Decision Fatigue: Shoppers face difficulty selecting garments that suit their
preferences and body types.

Limitations of Existing Solutions

Existing try-ons lack realistic draping, texture mapping, and adaptability to body types.

Consumers rely on inconsistent sizing charts, leading to mismatches.
Current e-commerce platforms offer static catalogs with minimal customization options.
Designers do not have an AI tool which can take real world design attributes as input and
generate a garment image virtually. A garment generation and virtual tryon solution tailored
to India's use case does not exist.

Benefits and Drawbacks of AI-Based Approach

Benefits:
• AI-driven diffusion models provide high-quality, dynamic visualizations of clothing.
• AI suggests designs tailored to user preferences.
• Reduced returns and optimized production contribute to environmental conservation.
• Digitization of traditional designs expands market access.
• Helps designers look how their imagined design will look in the real world even before
any production begins.

Drawbacks:

1. Requires high-end processing power for real-time rendering.

2. Storing user images raises ethical and security challenges.

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