SAP Startup Spotlight: Stylumia

An experienced retail professional, Ganesh Subramanian has had long stints in supply chain leadership roles with global and Indian fashion and general merchandise retailers. For example, he was the Chief Operating Officer of India’s largest fashion e-tailer Myntra. Ganesh Subramanian is also the founder and CEO of Stylumia, a deep technology venture solving real-world problems in fashion and lifestyle businesses using cutting-edge artificial intelligence. In this interview, he explains how his company is helping customers transform and how it is connected to SAP.

E-3 Magazine: What exactly does Stylumia offer?

Ganesh Subramanian: Stylumia offers three solutions answering three fundamental questions in any fashion and lifestyle brand: Which trends should we adopt? How much should we produce? And when and where should we distribute our product? The three solutions are called Stylumia C.IT, Stylumia Apollo, and Stylumia Store.Y. They are powered by a proprietary AI/ML demand sensing engine and Stylumia’s Taste-Model for better understanding and anticipating consumer behavior. We enable brands and retailers across the value chain, ranging from design, buying, merchandising, and allocation, to make informed decisions, eliminate guesswork, and reduce waste. We also have an innovation lab within Stylumia, which is always looking into the future. We recently announced the arrival of our design assistant, Stylumia ImaGenie, which helps designers create product ideas.

How does your solution work?

Subramanian: Our C.IT (Consumer Intelligence Tool) solution collects data at internet scale, using a proprietary one-of-its-kind demand sensing engine, removing the noise and revealing true consumer demand signal. This tool is primarily used by designers, buyers, and merchandisers for accurate trend and product forecasting. Stylumia Apollo is a unique “crystal ball” of sorts for predicting demand of unseen new products, which is the most challenging use case in fashion. Our prediction model uses both image and text to predict. Stylumia Store.Y helps drastically improve speed and accuracy of merchandise allocation to stores using a unique Taste-Model which predicts demand of a product in the context of an assortment. The solution also encompasses dynamic clustering.

Why did you found Stylumia?

Subramanian: I founded Stylumia with a mission of reducing waste in the fashion and lifestyle industry. The waste in the fashion industry globally amounts to over 750 billion U.S. dollars every year due to oversupply – which is exactly the supply demand gap that Stylumia aims to close.

How are you connected to SAP?

Subramanian: We were one of the startups chosen in the data and analytics accelerator program of SAP.io Berlin. We have since graduated from the program.

What’s next for Stylumia?

Subramanian: We want to impact the fashion and lifestyle sector on a global scale. We started expanding into the United States, the United Kingdom, and Australia. On the product side, we will be investing in research continuously and look at category expansions beyond fashion and lifestyle. We keep getting inquiries from industries like automobile, food, CPG, and many more. What we do is, at its core, category agnostic. For the time being, however, we will stay focused on fashion and lifestyle.

Thank you for the interview.

Enjoyed this article in our SAP Startup Spotlight Series? You might also like our piece on Heuritech, a startup providing solutions to fashion brands with an AI-based trend forecasting approach.