Grid Dynamics recognized as Google Cloud leader by Everest Group

Inventory management

Provide fast access to accurate inventory information across channels with a high-performance omnichannel inventory engine. Start modernizing the fulfillment ecosystem by strangling legacy monolithic order management systems.

How does our inventory management solution work?

For the last 10 years, we’ve been helping Fortune-1000 retailers, brands, and CPG companies modernize their inventory management capabilities to deliver an omnichannel commerce experience. Our goal has always been to build a truly unified platform that can provide an accurate view into the enterprise inventory, can serve the digital and in-store customer experience, and handle availability updates in real-time.

How does our inventory management solution work?

In addition to operational support of inventory management, we provide state-of-the-art algorithms for smart order sourcing to optimize shipment cost and time. We use AI-powered safety stock optimization software to balance demand and inventory utilization between in-store and online orders.

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Building an e-commerce omnichannel inventory solution with open-source
In this article, we describe the challenges that modern retailers face with omnichannel inventory management. We show a blueprint with reference architecture and approach to modernizing inventory management capabilities in two steps.
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Will “Database as a Service” work for retail inventory management?
This article focuses on using the cloud database as a service technology to implement an omnichannel inventory management platform. We evaluate technologies from three major cloud providers (GCP, AWS, and Azure) from functional and performance perspectives and explore their viability for the use case.
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Safety stock optimization for ship-from-store
In this article, we describe the inventory optimization problem for the buy-online, pickup-in-store and ship-from-store use cases and provide a case study that shows how stock levels can be optimized in real-life settings using machine learning methods.
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