Jellibeans, a fashion intelligence and analytics start-up co-founded by Joanne Chow and Brian Marsh, has launched Jelli.studio, an AI-powered fashion design-to-production platform.
The new platform enables rapid prototyping and optimisation of collections in just 30 seconds. Fresh from a USD1 million investment from Aussco, a leading knitwear supplier, Jelli.studio aims to bridge the gap between fashion and data and is described by its founders as “Canva, Bloomberg Terminal and Midjourney rolled up into one platform” for the fashion industry.
Combining fashion design with data analytics and AI image generation capabilities, the platform caters to both independent designers and established brands, integrating sales data with trend forecasting for better decision-making and transparency.
Retail in Asia talks to co-founder Joanne Chow on her ambitions for the fashion industry and how Jelli.studio can empower designers and brands alike.
RiA: Tell us a bit about your background and how you came to establish Jellibeans.
Joanne Chow: I started my career as a strategist within the fashion industry for major fashion labels, which I occasionally felt held limited sway in the grand scheme of things. So that uneasiness prompted my foray into entrepreneurship with the aim of looking to make a more substantial impact. During the past decade, I’ve set up a research and development lab focused on material innovation and also launched A Matter of Design, a business best known for lifestyle retail and distribution of both fashion and furniture brands [such as] Tom Dixon and BoConcept.
The inception of Jelli.studio came when the entire fashion world and supply chain were disrupted by Covid-19. Compounding the existing challenges in the fashion industry, Covid-19 further complicated the collaboration process between fashion brands and manufacturers by introducing travel and shipment restrictions as a result of the pandemic. This drove me to come up with the idea of jelli.studio, a AI-powered design-to-production collaboration and intelligence platform that helps fashion brands tackle persistent industry challenges as we navigated the pandemic.
RiA: How did you arrive at the idea of Jellibeans – and now Jelli.studio?
Chow: Jellibeans started out with a consumer-facing fashion discovery platform jellibeans.com, that boasts a user base of hundreds of thousands of people. Yet as the fashion market swelled with new entrants and complexities heightened during the Covid-19 pandemic, we realised the unique potential for the insights we had into consumer fashion trends aggregated over the last three years. Our seasoned expertise and knowledge would prove valuable to fashion’s global forecasting and brand portfolio management. With growing interest in e-commerce, for example influencers looking to diversify their revenue streams through launching fashion brands, we recognised an opportunity to offer a go-to platform for designers of any size to conceptualise, design and collaborate with suppliers to bring their designs to life.
This is where Jelli.studio comes into play. It offers a distinctive B2B model tailored for new or even established fashion brands, one that emphasises brand portfolio management, collaborative ventures, and the digitalisation of the direct-to-consumer processes. Plus it offers perks like the ability to automatically generate designs from scratch based on trending collections, and optimise designs that users can submit to make the collections more sellable.
Through harnessing our robust data infrastructure, and AI technological capabilities, we believe this strategic shift will establish us as a leading force in the fashion industry, adept at resolving persistent issues in the fashion world.
RiA: Who is the platform’s primary audience, and how is this designed to empower them?
Chow: Jelli.studio was created for designers or owners of fashion brands of all sizes that enables creative minds – designers, buyers, and planners – who are increasingly searching for accessible tools that enable them to provide data-backed decision-making. There is a disconnect between what fashion creatives think would sell and what actually does end up selling, and this is the gap that Jelli.studio fills. Designs based on a hunch typically result in unsellable inventory and massive waste. So, with jelli.studio, we aim to help fashion brands optimise their ROIs by integrating quantifiable insights into their creative processes.
Social media like Tiktok has led to the rise of micro fashion trends, more often than not falling out as quickly as they surge in popularity. We’re here to provide brands with insights, identifying valid trends from noise. Last but not least, this intelligence platform also equips fashion buyers with knowledge and data to engage in informed and productive dialogues with suppliers.
RiA: How is Jelli.studio utilising generative AI?
Chow: Jelli.studio harnesses the power of AI-driven generative design to help brands optimize their collections’ sellability and plan for open-to-buy items.
To train the AI and offer the industry’s most comprehensive business intelligence data infrastructure, Jelli.studio performs trend analysis and forecasts with historical data from more than 10 million products from more than 100 data sources – including outlets, retailers, fashion brands, resellers, social media, and Web 3.0. This does not only follow trends but also predict what’s statistically likely to perform well in the market.
On top of this, our generative AI technology enables users to simply upload files of their existing designs and tap into Jelli.studio’s data-driven optimisations to ensure commercially viable collections. Or they can create an entirely new, sellable collection from scratch with just a click. This groundbreaking AI feature allows Jelli.studio users to generate or refine collections in a fraction of the usual time.
It leverages data and AI to transform the design process, which traditionally takes a minimum of three months for a collection with a design team of up to five people.
One essential feature is our AI benchmarking tool that serves as a plagiarism checker, enabling users to detect any inadvertent similarities with existing market designs, taking into account critical factors such as cost, materials, and design elements.
Apart from bolstering market awareness, this feature also fosters originality. It helps brands create unique, trend-responsive pieces without falling into imitation. By harnessing AI in this manner, brands can maintain their authenticity while effectively responding to changing fashion trends and demands.
RiA: What else is next for you?
Chow: We’re particularly excited about the prospect of seamlessly integrating with e-commerce platforms, enabling brands to effortlessly import their data into our system.
Jelli.studio’s architecture itself is scalable and even capable of being customised to integrate existing sales CRMs with Jelli.studio. This means that the brand’s sales data can be collated with Jellibeans’s industry-leading and comprehensive trend forecasting data infrastructure. This in turn not only optimises jelli.studio’s design recommendations and analytics and offers better data-driven decision making throughout the design-to-production workflow, but also offers improved transparency and collaboration among the brand’s stakeholders, including the designer and suppliers.
This would represent a significant step towards simplifying and streamlining the fashion industry’s data management processes, ultimately allowing brands to make more informed and strategic decisions, and enhancing their overall performance in the market.