STCH Raises $7M To Build AI-Led Fabric R&D Platform
STCH, a Bengaluru-based textile tech startup, raised $7 million in a pre-Series A round led by Omnivore, with participation from Kae Capital and WVC. The company operates a CDMO model that combines AI-driven trend detection, materials selection, and a controlled manufacturing network to develop sustainable, trend-aligned fabrics for global fashion brands. STCH plans to use the capital to expand its AI stack, build a dedicated fabric R&D lab, deepen relationships with textile mills across India and Asia, and scale delivery to key markets in the UK, Europe, and the US. The startup cites an order book above $15 million and founders with prior Zetwerk experience, positioning STCH to industrialize fabric innovation at scale.
What happened
STCH raised $7 million in a pre-Series A round led by Omnivore, with participation from Kae Capital and WVC. The Bengaluru-headquartered startup is building an CDMO platform that integrates AI-led fabric R&D with a controlled manufacturing network to deliver sustainable, trend-aligned textiles to global brands. STCH states an order book in excess of $15 million, and founders Narahari Payala and Aseem Chitkara bring prior operational experience from Zetwerk.
Technical details
STCH combines data-driven trend detection, materials science inputs, and supply-chain orchestration into an AI stack focused on fabric innovation. The immediate use of funds targets AI capability expansion and an on-site fabric R&D lab to iterate on weave, finish, and sustainable-fiber formulations. Key near-term priorities include:
- •expanding AI capabilities for trend forecasting and material selection
- •building a dedicated fabric R&D lab to validate formulations and processes
- •deepening partnerships with textile mills across India and Asia to control quality and scale
- •scaling delivery and compliance for customers in the UK, Europe, and the US
Context and significance
Fabric is a high-leverage, historically under-optimized layer in fashion supply chains; improving it touches cost, performance, sustainability, and time-to-market. STCH's approach moves beyond front-end retail AI to the manufacturing core, creating end-to-end coupling between trend signals and factory execution. The founders' Zetwerk background gives domain credibility for negotiating mill networks and large-volume contracts. Trade dynamics and renewed focus on sustainable inputs make this a timely capital deployment for India-based manufacturing to capture higher-margin, design-sensitive work.
What to watch
Execution will hinge on the R&D lab producing repeatable, scalable fabric recipes and on converting the stated $15 million order book into on-time deliveries. Monitor follow-on funding, partnerships with major fashion brands or mill consortia, and measurable sustainability metrics (recycled-content percentage, lifecycle CO2, water usage) as leading indicators of product-market fit and impact.
Key Points
- 1STCH raised $7 million to scale an AI-driven CDMO for fabrics, targeting R&D, mill partnerships, and global delivery.
- 2The startup links trend forecasting to materials science and controlled manufacturing, addressing a poorly optimized textile layer.
- 3Execution risk centers on lab-to-factory transfer, converting a $15 million order book, and proving measurable sustainability gains.
Scoring Rationale
This is a solid, sector-specific funding event: relevant to practitioners working at the intersection of materials, supply-chain, and applied ML but not a broad platform or model breakthrough. The founders' domain experience and an existing order book increase its practical relevance for industry deployments.
Sources
Public references used for this report.
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