Supply Chain Innovation & Technology

unspun Is on a Mission to Tailor Fashion Production

The startup’s FitOS platform recommends the perfect sizes to customers and helps brands tailor their fit and inventory accordingly.

Published 4 weeks ago | About a 3 minute read

Image: Kaboompics.com

Sustainable fashion tech startup unspun has launched FitOS — a suite of software tools designed to transform how brands and consumers approach apparel sizing and fit. Aimed at boosting conversion rates, minimizing returns and enhancing customer experience, FitOS enables fashion brands to meet modern consumers’ expectations with precision and eliminate the industry’s notorious levels of waste.

Other startup innovators are working to design out this waste by completely remolding fashion; and REI has joined the growing number of apparel brands embracing a more inclusive range of sizes. But the industry at large is still centered around limited sizing that fails to reflect the diversity of real body shapes — as well as rampant overproduction — which have created an industry-wide crisis of returns and clearance stock. According to the National Retail Federation, consumers returned $817 billion worth of products in 2023 — a significant portion of which was attributed to poor fit. Alarmingly, up to one-third of returned clothing is destroyed — contributing to waste and fashion’s notoriety as one of the world’s most polluting industries.

unspun is taking a multi-pronged approach to designing an intentional, waste-free future for fashion: First, through its zero-inventory, on-demand brand of AI-tailored blue jeans. Second, by inventing the world’s first 3D weaving technology for apparel: Vega™ — which can weave garments from yarn within minutes — addresses the waste associated with overproduction by enabling nearshoring and on-demand production. But the certified B Corp knew more could be done.

“There’s only so much reach that we at unspun can have,” Dan Robichaud-Carew, unspun’s head of software product, told Sourcing Journal. “We have cool tech; they have a problem.”

Now, FitOS uses unspun's proprietary technology to recommend the perfect sizes to customers and help brands tailor their fit and inventory accordingly — aiming to provide industry a new solution in personalized sizing recommendations; and ultimately, create fast, clean, resilient fashion supply chains with cost-competitive production and superior inventory management.

For customers

Shoppers fill in a survey or do a body scan: Customers either fill in a survey or perform a 30-second scan using their smartphone, creating a detailed 3D model with thousands of data points.
unspun analyzes the data: unspun’s proprietary algorithms synthesize these data points, analyzing not only static measurements but also body shape, proportions, and posture. This approach ensures each size recommendation is a precise match for the unique attributes of each consumer.
unspun provides a personalized size recommendation: FitOS provides specific size suggestions for each item, considering fabric, cut, and intended fit for unparalleled accuracy.

“We think [size recommendations] can really have a positive impact on reducing returns and getting customers to feel more confident in what they’re buying,” Robichaud-Carew said.

For brands

FitOS also offers brands insights that they can use to improve their design and production process:

Data-based design: Rather than using generic fit models, brands can access fit models built from their actual customers to inform design and pattern-making, creating better-fitting products.
Optimize inventory: Provides size curve and inventory recommendations, allowing brands to adjust their fits and stock proactively.
Custom patterning: If brands so desire, FitOS integrates with unspun’s custom patterning technology for customized on-demand production

unspun aims to chart a sustainable course for fashion by partnering with brands and manufacturers worldwide committed to streamlining and decarbonizing their supply chains through automated, localized, low-impact production.