How Manyavar Is Using AI To Take The Guesswork Out Of Retail

Manyavar is as much a technology and data company as it is an ethnic wear brand, claimed Vedant Modi, the company’s chief revenue officer. 

Speaking at a fireside chat at the seventh edition of Inc42’s D2C & Retail Summit in Gurugram, Modi cited several examples of how the brand leveraged advanced data analytics and AI to scale to over ₹1,000 Cr in revenue with margins exceeding 65%. 

One of the most lucid examples came when moderator Praharsh Chandra, cofounder and CBO of logistics firm Shadowfax, asked him to describe how the company uses data to drive decision-making. 

“Our taste as founders does not matter. So, that was the biggest learning we had… a lot of people obsess over their own taste. If you ask a designer if they have a great collection, they will say it’s great, and if no one bought the collection, they will say the market hasn’t evolved yet. For us, the biggest insight was: how can we look at a product from a data aspect?” said Modi. 

He explained that Manyavar doesn’t use traditional colour names like blue or black, instead breaking every garment down into a collection of subcategories such as colour, texture, fabric, design type, and numeric codes designating each option within the subcategory. 

This, in turn, is used to automate store-level inventory allocation based on data about consumer trends. 

“South Delhi and Karol Bagh behave very differently because very different sets of customers are walking into our stores. Even within Delhi, only 35% of our inventory from a design angle would be common between these two locations,” said Modi, adding that 70-75% of decisions are taken by algorithms, and the remaining edge cases are taken by AI. 

He added that Manyavar aims to sell through 90% of the inventory it supplies to any store. Here, too, automation and data-driven algorithms are crucial to achieving this critical performance metric. 

“Our system automatically starts to understand if a product is doing well somewhere, but not elsewhere, and will automatically send it from one store to another,” he said. 

While this clears a further 7% of inventory, the remainder is typically donated as dead stock, which enables the brand to maintain its premium pricing without resorting to discounting. 

Manyavar has also taken two decades’ worth of historical data, almost 85 Cr data points, and uploaded it to a Model Context Protocol (MCP) server that connects to its deeper AI systems, Modi noted. 

Modi said that the brand’s overall growth was increasingly being driven by their ability to turn data into decisions — from product design and inventory allocation to store-level performance. By combining granular data, automation and AI, the brand is reducing guesswork, improving sell-through and protecting margins, showing how technology can become a core competitive advantage in traditional retail.

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