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Inventory on Track as Iguazio and Trax Partner with Google Cloud

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This week at Kubecon in Seattle, Iguazio announced it is partnering with Google Cloud to bring real time AI to retail inventory management. Google Cloud and Iguazio’s hybrid cloud is enabling Trax, a provider of computer vision and analytics solutions for retail, to leverage Kubernetes and a cloud-native architecture without managing its underlying infrastructure.

The announcement comes in a season where retail shopping is on the rise, even in bricks and mortar stores, which are working in more interesting ways with their e-commerce platform.

This new combination was designed to improve the supply chain while also now reaching the Consumer Packaged Goods (CPG) shelves, sharing analytics with retailers and their wholesale providers.

The retail solution includes image recognition and predictive analytics.

Even during the peak holiday season, store margins are under intense competitive pressure. Out-of-stock can make or break a retailer’s bottom line. Real time analytics are important as most analysis and responses to out-of-stock and shelf shrinkage are backward-looking. The data, over time, is useful for long-term mitigation, but is less effective in organizing real-time response

Inventory management systems (IMS) capture data about incoming goods using a variety of technologies - RFID, barcodes, and even manual checklists. By subtracting sales recorded at point-of-sale (POS) terminals, adding returns and adjusting for other inventory transactions, the most advanced IMS systems track sales-floor and back-room inventory at the SKU level.

These systems have gaps and drive the painful physical inventories to get to the correct numbers. Physical counts are badly out of date by the time they’re compiled and can’t be used to guide real-time, adaptive measures.

A variety of solutions are often kluged together by larger retailers including POS analytics, video surveillance, sensors, RFID and more. By integrating multiple retail technologies and data, inventory optimization is possible. When the in-store approaches are extended to the suppliers, even more optimization is possible.

“At Trax, we’re digitizing the world of retail by monitoring, predicting and optimizing store-and-field performance in real-time to improve on-shelf availability, optimize click-and-collect processes and modernize the shopping experience,” said Trax Chief Technology Officer, Yair Adato. “We recognized that we needed an edge-to-cloud solution that was built for speed, scale and intelligence – one that allowed us to focus on our application, versus the management of our infrastructure.”

“Kubernetes exemplifies the power of the consistent platform where customers appreciate learning once and use anywhere. Building applications on top of Kubernetes ensures companies can deploy workloads either on premises or in the cloud of their choice,” said Aparna Sinha, Group Product Manager, Kubernetes and GKE, Google Cloud. “The retail industry requires data portability across the cloud and intelligent edge. We are excited to collaborate with Iguazio to deliver a solution that enables real-time analytics of store data, all centrally managed from Google Cloud.”

Trax solutions require real-time data processing at the edge from hundreds of shelf-mounted cameras, operational systems and even autonomous robots throughout retail chains. Iguazio provides an integrated platform with a variety of data services, managed Kubernetes and serverless functions, which is controlled and monitored from Cloud IoT Core, all seamlessly integrated with Google Cloud data and messaging services.

The combination of Iguazio’s managed platform and Google Cloud services enables the collection and analysis of large 2 volumes of data at the edge, while leveraging Google Cloud for deep learning, AI, data aggregation and central control.

“Iguazio extends the cloud experience to the edge,” said Iguazio’s CEO, Asaf Somekh. “The intelligent edge is trending across a variety of industries, as the market begins to use the power of the cloud for training and data science, while prioritizing real-time decisions at the edge.”

Iguazio’s edge is cloud-native and powered by Kubernetes. The platform includes data services and AI tools, running serverless functions with Nuclio to reduce bandwidth constraints by sending only filtered and aggregate information to the cloud.




Edited by Ken Briodagh
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