ShelfMind
ShelfMind
ShelfMind is building the future of automated retail execution — where every shelf is optimized, every product is placed with intent, and every decision is backed by real data.
For years, retail teams have struggled with static planograms, manual updates, and disconnected data. Brands and retailers lose millions each year because shelves don’t reflect reality — fixtures differ by store, products vary by region, and human-driven layouts can’t keep up with dynamic demand.
ShelfMind was created to solve this problem at scale. Our platform automates planogram building using real performance data, product attributes, and store-specific fixtures. The result: faster resets, better space utilization, and layouts that actually improve sales instead of relying on guesswork.
To empower retail organizations with AI-driven precision, making shelf execution faster, smarter, and measurable — without adding operational complexity.
Data-driven layout generation that adapts to store size, fixtures, assortment, and performance trends.
Identify underperforming shelves, gaps, and opportunities through rich analytics.
Built on Azure with security, scaling, and availability expected by enterprise retailers.
ShelfMind was founded by Pradeep Kumar Singh after years of building large-scale assortment, space, and planogram automation systems that most teams would need 10–15 specialized roles to handle. The vision is simple: bring that level of sophistication to every brand and retailer through a clean, modern, automated platform.