Every that was easy shopping moment is made possible by teams working to hit shipping deadlines, scrambling to fix missing product details and striving to provide curated shopping experiences.Behind the scenes, workers are dealing with the reality of aging systems, siloed data and rising customer expectations - a combination that makes consistency and speed harder to deliver with every new season and added stock-keeping unit (SKU).
New Multi-Agent Intelligent Warehouse (MAIW) and Retail Catalog Enrichment NVIDIA Blueprints are designed to turn this dynamic system into an advantage. These open-source developer references, launched today, empower developers to customize AI-powered solutions for the retail value chain, from warehouse to wardrobes.
Building with these blueprints will reduce the cost of integration and help our customers and partners enable applications fast, said Tarik Hammadou, director of developer relations for AI for retail and consumer packaged goods at NVIDIA. They unlock the efficiency and enterprise grade scale the retail industry needs to compete.
The blueprints will be showcased next week at the National Retail Federation: Retail's Big Show.
Easing Warehouse Workflows Warehouses are dynamic spaces with many moving parts, from boxes carrying a variety of retail goods to massive machines and workers fulfilling thousands of daily orders. Issues can arise in an instant - from out-of-stock items to cleanups needed in aisle four.
An ongoing issue within this workspace is a disconnect between the IT and operational technology (OT) layers. This gap bars managers from easily handling problems such as accurately measuring product inventory, efficiently pinpointing technology issues and deploying enough workers to areas that need extra help.
The idea of having an agentic AI layer on the IT or OT level is not efficient, but having agents in between IT and OT allows the AI agents to act as the coordinators, said Hammadou.
A look inside the MAIW Blueprint. The NVIDIA MAIW blueprint delivers a synchronized AI system that sits above existing warehouse management systems, enterprise resource planning, robotics and IoT data, so teams gain real-time, explainable operational intelligence.
The blueprint comprises specialized agents for equipment asset operations, operations coordination, safety compliance, forecasting and document processing - all orchestrated by a central warehouse operational assistant that mirrors how warehouses actually run and turns fragmented data into proactive decision-making.
For example, a supervisor can ask in natural language, Why is packing slow? and the assistant analyzes equipment status, tasks queues and staffing data to highlight the bottleneck, shows the supporting evidence and recommends actions such as rebalancing work or adjusting task priorities.
The blueprint also provides production-grade capabilities - including role-based access control and guardrails to keep recommendations within policy - so operations teams can trust AI to help coordinate real equipment and safety-critical decisions.
By targeting metrics to detect and resolve issues and safety incidents, as well as ensure on-time order fulfillment and service level agreement adherence - MAIW helps warehouses move from constant fire drills to more predictable, data-driven shifts.
Partners such as Kinetic Vision, a product and technology development firm, can use the MAIW blueprint to innovate and tackle decades-long issues in retail supply chains.
Chart and graphs are yesterday, we need predictions and prescribed actions, said Jeremy Jarrett, CEO of Kinetic Vision. The NVIDIA MAIW blueprint would allow you to have more of a central way to answer questions and prompt decision-making.
Resolving Sparse Product Data The Retail Catalog Enrichment NVIDIA Blueprint can help businesses of all sizes achieve richer and accurate product onboarding, as well as deliver localized marketing.
Retailers often face a sparse data problem: product images arrive with minimal or inconsistent text, and teams spend large amounts of time writing titles, descriptions and attributes, then customizing them for each market and campaign.
The blueprint addresses this by using generative AI to create high-quality, structured, localized and brand-aligned product content at scale.
For example, imagine a home goods retailer trying to update their online storefront with a basic set of ceramic mug photos. With an NVIDIA Nemotron vision language model (VLM), part of the Retail Catalog Enrichment Blueprint, the photos can be fed through the VLM to develop product metadata such as color, material, capacity, style and use cases.
From a single image, the system can then generate localized product titles and descriptions, extract and normalize attributes for search and recommendation systems for improved SEO and GEO, and create culturally relevant 2D lifestyle imagery and interactive 3D assets. Behind the scenes, an AI judge checks outputs for quality and consistency.
In addition, the Retail Catalog Enrichment Blueprint can create rich, on-brand marketing content by applying brand voice, tone and taxonomy instructions via prompts, alongside the product image and a target locale. The blueprint uses those brand guidelines to generate enriched product titles and descriptions, localized categories and tags, and culturally appropriate lifestyle image variations tailored to that intent.
Grid Dynamics' NVIDIA Blueprint-Powered Solution Companies are already creating their own products with the help of NVIDIA's retail blueprints.
Global tech consulting firm Grid Dynamics has built a catalog enrichment and management system that increases the accuracy of item content and status of SKUs for large retailers, using the Retail Catalog Enrichment NVIDIA Blueprint.
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