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Scaling Retail Shelf Recognition with IBM

Key Points

  • Maksim Morozov, CEO of an Eastern‑European intelligence‑retail tech firm with operations in Finland and Russia, highlights the persistent “out‑of‑shelf” problem in brick‑and‑mortar stores.
  • Missing items, incorrect pricing and outdated promotions cost the retail industry over $500 billion each year, prompting the company to develop a visual‑recognition platform that can instantly flag stock‑outs.
  • The solution must handle massive image‑processing loads—from tens of thousands to tens of millions of photos monthly—and be easily scalable across new regions and markets.
  • To meet these reliability and big‑data demands, the firm selected IBM’s infrastructure and analytics services as the backbone for its global rollout.

Full Transcript

# Scaling Retail Shelf Recognition with IBM **Source:** [https://www.youtube.com/watch?v=2hlvVAOdxw4](https://www.youtube.com/watch?v=2hlvVAOdxw4) **Duration:** 00:01:36 ## Summary - Maksim Morozov, CEO of an Eastern‑European intelligence‑retail tech firm with operations in Finland and Russia, highlights the persistent “out‑of‑shelf” problem in brick‑and‑mortar stores. - Missing items, incorrect pricing and outdated promotions cost the retail industry over $500 billion each year, prompting the company to develop a visual‑recognition platform that can instantly flag stock‑outs. - The solution must handle massive image‑processing loads—from tens of thousands to tens of millions of photos monthly—and be easily scalable across new regions and markets. - To meet these reliability and big‑data demands, the firm selected IBM’s infrastructure and analytics services as the backbone for its global rollout. ## Sections - [00:00:00](https://www.youtube.com/watch?v=2hlvVAOdxw4&t=0s) **Scaling AI Shelf Recognition** - CEO Maksim Morozov describes how his Eastern‑European retail‑technology company tackles costly out‑of‑stock issues by processing massive volumes of shelf‑photo data for real‑time product recognition, and why they selected IBM’s robust big‑data infrastructure to scale the solution globally. ## Full Transcript
0:01my name is Maksim Morozov I'm chief 0:05executive of intelligence retail company 0:07so we're a technology company from 0:09Eastern Europe we have a presence in 0:11Finland and Russia there's a big 0:13challenge still in in brick-and-mortar 0:16retail we are all shoppers right and 0:18when we visit stores we expect a 0:20well-organized shelf so it means that 0:23all the products should be at the shelf 0:24so prices should be correct so 0:27promotions are not outdated and that's a 0:30big problem number one problem for 0:32retail now it costs more than 500 0:35billion every year if the product is 0:37missing for example if the product is 0:39out of shelf and you don't know it every 0:41minute you lose money that's what we try 0:44to fix it means that we need more 0:46recognition power on our servers for 0:49example if the customer starts in one 0:51region and they start to send us like 0:54100,000 follows per month they can 0:58easily roll out the solution to to other 1:00countries to other regions and increase 1:02in this number up to some Millions we 1:05now know that we can support easily any 1:07projects any size of the customer and we 1:11can easily scale rollout to other 1:14countries and other regions we are not 1:17afraid now if the customer send us you 1:19know ten millions photos to be 1:21recognized we know that infrastructure 1:22is allows us to do and end to scale our 1:27recognition power we need a reliable 1:29infrastructure and big data solutions 1:31that's why we at the end we chose IBM