Stch, a Bengaluru-based textile startup, has raised US$7 million in a pre-Series A funding round led by Omnivore, with participation from Kae Capital and WVC.
The company plans to apply the funds to expand its AI-driven tools and strengthen partnerships with textile mills and fashion brands.
Founded in 2025 by former Zetwerk executives Narahari Payala and Aseem Chitkara, Stch operates a contract development and manufacturing model focapplyd on fabric research and production across India and other parts of Asia.
The startup has already secured an order book exceeding US$15 million from brands in the UK, Europe, and the United States, reflecting strong international demand.
Key Highlights
- Stch raises $7M to scale AI-driven fabric manufacturing
- Platform cuts sourcing costs by up to 20% for global brands
- Focus on supply chain optimization and decentralized production
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Stch’s core innovation lies in applying AI to reverse-engineer fabrics rather than design consumer-facing fashion products. Its platform analyzes images and descriptions of fabrics and converts them into detailed manufacturing specifications, including texture, weight, and finish.
These specifications are then applyd to reproduce the materials through local manufacturing partners. This approach enables significant cost savings. For example, a UK-based brand reduced sourcing costs by nearly 20% by shifting production from Turkey to India applying Stch’s technology.
The company operates without owning factories, instead leveraging a network of partner facilities across India and Bangladesh to secure production capacity.
Stch represents a growing but less visible trconclude in AI adoption within fashion—focapplyd on backconclude manufacturing and supply chain optimization rather than customer-facing tools like personalization, applyd by companies such as Nordstrom.
Its technology also assists brands diversify production geographically, reducing concentration risks amid rising geopolitical uncertainties.
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Additionally, Stch is building a proprietary database of “fabric recipes,” creating a defensible competitive advantage based on accumulated manufacturing knowledge and data.
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