How STCH Is Modernising Apparel Manufacturing With AI & Factory OS

India’s D2C fashion ecosystem has become exceptionally good at spotting trends. Brands today use AI to generate hundreds of new designs in a matter of hours, identify emerging consumer preferences and launch collections at a speed that would have been unimaginable a few years ago. Manufacturing, however, moves at a snail’s pace.

Turning a design into a finished garment takes four to five months, forcing brands to lock up crores of rupees in inventory before they know whether a product will sell. As fashion cycles shorten, this mismatch is becoming one of the apparel industry’s biggest operational challenges.

Bengaluru-based STCH believes the problem isn’t India’s manufacturing capacity but the way manufacturing is organised. 

Founded in 2025 by ex-Zetwerk executives Narahari Payala and Aseem Chitkara, the startup is building a technology-led contract manufacturing platform that combines AI with factory operations to help brands develop products faster, manufacture in smaller batches and replenish inventory based on demand. 

In doing so, it hopes to modernise an industry that remains one of the largest beneficiaries of the China+1 shift but continues to grapple with fragmented supply chains and limited visibility across production.

Unlike most apparel technology startups, which have focused on helping consumers discover or buy fashion, STCH is building for an audience that rarely gets attention from software companies: the manufacturers. 

The founders argue that while AI has reduced the time it takes to design products, the manufacturing layer has remained largely unchanged. Solving that bottleneck could prove more valuable than building yet another consumer-facing fashion app, as per Payala. 

This thesis emerged after a UK-based apparel brand approached the duo for an alternative to fabrics it had been sourcing from Turkey. After recreating the material using Indian suppliers, STCH claims to have helped the customer reduce sourcing costs by nearly 20%, validating a larger opportunity around technology-led manufacturing.

From Design To Dispatch 

The startup works with fashion brands much before a garment reaches the factory floor. Instead of coming in only as a contract manufacturer, STCH starts at the product development stage, helping brands identify emerging trends, decide which products to launch and determine the materials best suited for them. 

From there, it manages fabric sourcing, sampling and manufacturing through a network of partner factories, giving fashion brands a single platform to oversee the entire process from design to dispatch.

Much of this workflow is powered by the startup’s in-house technology stack. Its AI models analyse fashion trends and customer demand to help brands shortlist products with a higher probability of success. 

Once a design is finalised, STCH’s proprietary fabric intelligence engine ‘FabricGPT’ recommends suitable materials based on parameters such as cost, performance, availability and sustainability. According to the startup, its platform draws on data collected from textile mills, testing laboratories and manufacturers to simplify what has traditionally been a manual and experience-driven process.

The final layer is further trying to modernise the apparel manufacturing process on the factory floor itself. STCH’s Factory OS combines workflow software with cameras and IoT devices to track production, monitor quality and improve visibility across partner facilities. The platform also enables factories to standardise operations and identify bottlenecks before they affect production schedules.

By connecting these stages through a single workflow, STCH says it has reduced product development timelines from nearly five months to about 45 days. This, in turn, allows brands to produce closer to demand, replenish successful products faster and reduce the amount of capital locked up in inventory, an increasingly important advantage as fashion cycles continue to shorten.

For apparel brands, STCH’s value proposition extends beyond shorter production timelines. The startup’s business model allows customers to move away from the traditional practice of placing large manufacturing orders months in advance and instead produce in smaller batches, using sales data to replenish successful products. According to STCH, this helps brands reduce inventory risk while responding more quickly to changing consumer preferences.

“The biggest shift we’re enabling is from forecast-led manufacturing to demand-led manufacturing. Brands don’t have to commit to large inventories upfront. They can start with smaller batches, understand what’s working in the market and replenish products that are seeing demand,” Payala said.

Building A Library Of Fabric Recipes

The startup is also investing heavily in fabric R&D, an area it believes has seen far less technological innovation than consumer-facing fashion. While most apparel manufacturers rely on fabrics already available in the market, STCH works with textile mills and fibre manufacturers to co-develop proprietary materials tailored to a brand’s requirements. 

These fabrics are engineered to balance performance, cost and sustainability, allowing brands to differentiate their products without investing in their own textile research capabilities.

At the heart of this is STCH’s library of fabric “recipes”, which is a proprietary dataset that maps combinations of fibres, yarns, manufacturing processes and finishing treatments. The startup has built this knowledge base by working with textile mills and suppliers, converting information that has traditionally remained fragmented and experience-led into structured data. 

This dataset powers FabricGPT, STCH’s in-house recommendation engine, which analyses product images and specifications to identify suitable materials and recreate similar fabrics using local manufacturing.

The startup claims that it has already developed cotton-based fabrics that replicate the look and feel of polyester, helping brands shift towards more sustainable materials without compromising on performance. According to Payala, the larger objective is to reduce the time it takes to move from identifying a fashion trend to engineering a fabric and then weaving it into production. 

“The textile industry has decades of knowledge, but much of it is scattered across mills and experts. We’re trying to organise that knowledge so brands can develop better products, faster,” he said.

STCH’s timing also coincides with a broader shift in global apparel sourcing. As brands diversify supply chains beyond China and recent trade agreements improve India’s competitiveness in markets such as the UK and Europe, manufacturers are under pressure not only to increase capacity but also to deliver shorter lead times and greater product flexibility. 

Scaling Without Owning Factories

STCH currently works with 18 apparel brands across India, the UK and Europe, including global fast fashion major Shein. All of which have placed repeat orders, according to the startup. STCH claims that it has built an order book of nearly ₹120 Cr, which will be delivered over the next year.

To support its next phase of growth, STCH raised about $5.5 Mn in pre-Series A funding from Omnivore, Kae Capital and others earlier this year. The capital is being deployed to strengthen its AI capabilities, expand its fabric R&D lab, deepen manufacturing partnerships and scale deliveries across key markets in India and Europe.

The startup currently operates through a network of partner factories across India and Bangladesh, with committed manufacturing capacity of around 1.2 Lakh garments a month. 

Rather than investing in its own production facilities, STCH integrates its technology into these factories and plans to scale capacity by onboarding additional manufacturing partners, allowing it to expand without taking on significant capital expenditure. 

Unlike traditional contract manufacturers that largely compete on price, STCH generates revenue by combining fabric development, product engineering and manufacturing into a single offering. 

Without disclosing actual numbers, STCH claims to see healthy gross margins and contribution margins. The startup attributes these margins to the higher value it creates through fabric R&D and AI-led product development. 

With a growing presence in the UK, which is its largest market, and expansion planned across Europe and the US, STCH is targeting a revenue of around ₹100 Cr in FY27. 

Execution, however, will determine whether that vision translates into a durable business. As STCH scales, it will need to maintain consistent quality across a growing network of manufacturing partners while proving that its technology can deliver measurable improvements for brands with vastly different sourcing and production requirements. 

Demand on the other hand will not be an issue for the startup, as global brands are increasingly looking beyond China, and India’s textile industry is well placed to benefit from this shift. But winning those orders will require more than adding manufacturing capacity. 

For STCH, the real test will be whether it can help make India’s apparel manufacturing industry faster, more responsive and better equipped for a market where fashion trends now change with Instagram reels rather than seasons.

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