The Big Problem that we solve
Fashion is over 2.7 trillion US$ market with 50% of the products not meeting consumer demand and selling on discounts creating a huge impact on revenue and profits. The value loss in itself is 750 billion USD. The fashion industry is the second most carbon footprint industries in the world just next to oil contribute to almost 10% of the total carbon footprint.
This is caused by a fundamental "Demand Prediction" problem (supply-demand gap). This the global challenge that we are solving.
We have a B2B SaaS platform using proprietary, one-of-its-kind Deep learning, Computer Vision & Prediction Models aimed at solving few fundamental challenges in fashion and Lifestyle brands and retailers to
“Validate: What to create/design? : Automate/Predict: How much to buy? And Where to distribute? : Create: How to create winning products?”
The current way of solving the problem is mostly subjective and expert-driven. We evaluated all the current practices and no one seems to be doing it right. We took it on ourselves.
Our unique approach is to transform this using demand-driven insights. We have a proven track record of this helping our clients (India and International) reduce inventory/carbon footprint by 25-40%, improve revenue velocity and profit by 30-50% on Stylumia driven products.
Our Solution
Highlights of the platform https://www.youtube.com/watch?v=47LNsccXP1U&t=2s
Stylumia MIT & Runway: Computer Vision for ranking global and local trends to take data-informed product decisions pre-season. Very unique in providing demand sense using our propreitary consumer Product Rank (like google ranks pages, we rank fashion products globally)
Stylumia FIT: Visual business Intelligence tool for client’s own-data solving the fundamental challenge of today’s analytics solutions which focus on text and numbers, this solution brings image, numbers and insights alive, helping manage in-season supply and demand.
Stylumia Apollo: Predicts fashion wins & losses before they undergo the test pre-season (using global futuire signals and contextual brand’s own data using both text and images), assigns demand rank for every product to a store location for optimising in-season revenue, inventory and profit
Stylumia Muse: One of its kind design generation engine to create winning design ideas using GAN's (Generative Adversarial Networks) with twice the probability of winning.
Area of focus of our idea/solution
Key areas of focus of the solutions are to address top questions faced by fashion and lifestyle industry which are
a) what products to spot?
b) what products to design?
c) how much to buy?
d) where to send?
Our solutions address them through big data with AI solutions which are consumer demand driven
What is unique/innovative about your idea – i.e. what differentiates you from other similar solutions or ideas:
Key Differentiators
Stylumia Market Intelligence Tool:
Intelligence starts by understanding what consumers want and what they do not. Stylumia MIT has a proprietary ranking algorithm (like that of Google page rank) to rank all fashion products globally on consumer demand at internet scale. This enables us to provide laser sharp contextual insights to our clients through the SaaS platform. We have a unique way to provide insights into consumer taste using computer vision covering all the visual attributes which is key in fashion decision making.
Stylumia Fashion intelligence Tool:
Most of fashion decision making is visual in nature and text cannot fully articulate fashion. This presents a great opportunity to have a business intelligence tool for the client’s own data (this also builds our data network). Stylumia FIT is a unique fashion intelligence tool to decode the taste of our client’s consumers by all key dimensions (geo and product) intuitively.
Stylumia APOLLO:
Placing bets in fashion is a gamble. APOLLO is one of the world’s first fashion predictor tool which can predict fashion wins and losses for unseen products. The bot is trained with the client’s past data and future signals from the market across retail, brand, social mediums. APOLLO’s prediction performs 1.5-2.0 times more accurate than human expert predictions.
Stylumia Muse: One of its kind design generation engine to create winning design ideas using GAN's (Generative Adversarial Networks) with twice the probability of winning.