Venture capitalists, as a group, aren’t exactly notorious for their keen fashion sense, but many have taken a strong interest in backing startups that thread AI technology into the apparel industry.

Overall numbers are still relatively small for this emerging sector, but venture investment in fashion-related AI startups has risen or held steady in the past five-plus years. That’s even as VC funding generally has fallen from its pandemic-era highs, Crunchbase data shows. 

Funding to startups at the intersection of AI and apparel spiked to $162 million in 2022 — when China-based Zhiyi Tech, which helps clothing brands spot and predict fashion trends, raised $100 million alone — and has clocked in around $100 million annually since then.

Investors’ interest in fashion-related tech makes sense, given that as a species, we’re estimated to spend an astonishing $1.8 trillion globally each year on attiring ourselves. That figure is projected to climb to $2.3 trillion by 2030.

The true economic and environmental costs of the fashion industry are of course much higher, by the time you account for production waste and pollution, the resources that go into shipping clothes halfway across the world, and frequent returns and exchanges — not to mention concerns about labor conditions in garment factories.

We identified dozens of companies operating at the fashion-and-AI intersection that raised venture funding in recent years, many of them working on issues such as more efficient manufacturing or faster trend-spotting. Some offer AI-driven creative design tools, others are focused on AI-enabled demand prediction or manufacturing, and several companies offer personalized shopping or customized garments. Let’s take a closer look.

Predicting fashion (before it’s no longer fashionable)

The best-funded startup at the intersection of fashion and AI appears to be Zhiyi Tech. The Xiaoshan, China-based company, which works with many China-based apparel companies, searches the internet and social media for trending designs, and combines that with sales data from e-commerce platforms to help brands quickly capitalize on viral trends.

Investors appear to be particularly eager to back companies that tap AI to predict fashion trends.

In the U.S., another top funding recipient is Finesse, which has raised close to $45 million total from investors. The Los Angeles-based startup describes itself as the “first AI-led fashion house” and creates fast-fashion clothes based on social media votes, shopping data and viral trends spotted by its machine learning technology.

“I call it ‘Zara meets Netflix,’ ” CEO and co-founder Ramin Ahmari told Crunchbase News in 2021, when the company raised its $4.5 million seed round. “We all love fashion and the beauty industry, but fashion is a huge world largely untouched by technology. There are now new trends in efficiency and data, and Finesse is all about using data to reduce the tons of waste in fashion.”

While reviews of its clothes have been mixed, the company went on to raise a $40 million Series A led by TQ Ventures.

Another well-funded startup in the fashion demand prediction realm is Syrup Tech. The New York-based company has raised $25.1 million total for its AI-driven predictive software used by fashion brands.

AI fashion design and creation tools

Fashion designers are also increasingly using generative AI to help them design clothes and make 3D digital mockups of items before they ever go into production.

Along those lines, funded startups include Raspberry AI, which earlier this year raised $24 million in an Andreessen Horowitz-led Series A. The New York-based startup’s platform turns designers’ sketches into photorealistic renderings, showing in rich detail how products will look, fit and drape in real life.

Another AI fashion design tool is AI.Fashion. The Los Angeles-based startup makes AI-driven tools for virtual photoshoots and fashion content creation. It raised a $3.6 million seed round led by Neo in February 2024.

BLNG, meanwhile, applies generative AI to jewelry design, converting sketches or text prompts into photorealistic 3D renders. The Los Angles-based company has raised $4.5 million, including a $3 million seed round in April, per Crunchbase.

Discovery and personalization

AI is also changing how consumers discover clothing and footwear. Startups in this category use machine learning to personalize recommendations, improve product tagging and offer smarter shopping experiences for consumers to help them better find what they want.

Among the most high-profile recently funded companies in this cohort is Daydream, an AI-powered shopping platform founded by e-commerce veteran Julie Bornstein, who previously founded The Yes and sold it to Pinterest three years ago. Her new startup makes personalized fashion recommendations through a chat-based interface. The San Francisco-based company raised a $50 million seed round in June from investors including Forerunner Ventures and Index Ventures.

Other companies in this subsector include Lily AI. Its platform translates retailer product attributes into more consumer-friendly language, with the aim of improving site search and personalization. The Mountain View, California-based startup has raised $71.9 million to date.

Other funded fashion discovery startups include:

• Tel Aviv-based Karma, which has raised $34 million in funding to date for its browser-based shopping tools;
• London-based Hey Savi, which raised $2.85 million in pre-seed funding last year for its AI fashion search engine; and
• Shoppin, an India-based startup that helps users discover clothing using prompts and images, raised $1 million in a pre-seed funding in January.

Virtual try-ons, precision fit and customization

Tracking down what looks like the perfect dress to wear to that summer wedding reception is one thing. Knowing it will actually fit and look good on you when it arrives is another.

Companies tackling that problem include several virtual try-on startups that aim to make it easier to gauge how a garment will fit before you buy it online — both to reduce buyer frustration and to reduce the chances of costly returns for retailers.

Along those lines, virtual try-on and social shopping app Doji last month raised $14 million in a seed round led by Thrive Capital. The San Francisco-based company’s app lets users create avatars for virtual try-ons of clothing.

Similarly, Paris-based Veesual offers diverse AI-generated virtual models to showcase how clothes look on different bodies. The startup has raised $7.6 million to date, mostly in a seed round last year led by AVP and Techstars.

A smaller subset of startups is working on actually personalizing the size and fit of shoes and clothes. Among the most notable of the bunch is New York-based IAMBIC, which uses AI to make precision-fit footwear. The company, whose completely custom sneakers were named to TIME’s Best Inventions list in 2023, has raised $1.3 million through research grants.

Another is New York-based Laws of Motion, a seed-funded DTC brand that has raised $10.2 million on the promise of precision-fit clothing for women through virtual body scans and AI technology.

Smart manufacturing and supply chain optimization

Other startups are turning to AI to improve the way garments are made. Funded companies in this group include those working on demand forecasting, advanced textiles and material optimization, process automation, and textile recycling.

For example, Smartex.ai installs AI and computer vision technology into textile factories to help them automatically detect textile defects. The Portugal-based startup has raised $27.6 million in funding, per Crunchbase.

Several startups focused on fashion-related sustainability have also raised funding in recent years. They include Matoha Instrumentation, which builds AI-enabled infrared scanners for rapid textile sorting to support recycling. The London-based startup raised £1.5 million in an April seed round.

Refiberd, meanwhile, uses AI and hyperspectral imaging to enable intelligent sorting in textile-to-textile recycling. The Cupertino, California-based company has raised $2.7 million total from venture rounds and grants.

There’s also some funding in the area of new textile technologies developed with the help of AI. One example is Solena Materials, which raised a $6.7 million seed round in May. The startup, also based in London, uses AI-driven protein sequence design to engineer new biodegradable fibers produced by microbes.

Looking ahead: AI will stay on trend

With AI overall en vogue with investors, startups weaving that technology into the fashion industry seem poised for more growth. We expect that as clothing brands continue to battle supply-chain pressures, consumer churn and shifting online behavior, AI tools will remain on trend in coming seasons.

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Illustration: Dom Guzman