Customer Service Automation · Real-time Analytics
Lowe’s needed to close product-expertise gaps for project-based shoppers and store associates, gain better visibility inside large stores, and modernize slow, expensive merchandising and planogram processes across its massive retail network.
Reported impact
Lowe’s reports 98 percent neutral-to-positive customer reactions to Mylow, 8,000 AI-assisted engineering code reviews per week, a 30,000-plus-item 3D asset catalog at under $1 per model, digitally updated twins for more than 1,750 stores, and faster, cheaper planogram experimentation that reduces physical reset work.
Lowe’s built a three-part retail AI platform that combines customer-facing assistants, associate tools, computer vision, and digital twins on NVIDIA technology. Mylow runs inside the Lowe’s app and website, where OpenAI models fine-tuned on Lowe’s proprietary data use retrieval-augmented generation and NVIDIA NeMo Guardrails to answer home-improvement questions with project steps, product recommendations, and real-time inventory context. The same engine powers Mylow Companion for store associates. At the physical layer, Lowe’s runs GPUs and micro-data centers built on Dell PowerEdge XR servers across stores so computer vision can spot when customers need help and alert nearby staff in real time. For planning and merchandising, NVIDIA Omniverse, OpenUSD, RTX workstations, the USD Search API, and Hyper3D.ai’s Rodin support digital twins of 1,750+ stores, AI-assisted 3D asset creation, and scenario testing for localized planograms before physical changes are made.
Customer and associate questions flow into Mylow and Mylow Companion, which use guarded RAG responses tied to Lowe’s product and inventory data, while in-store camera and edge systems drive computer-vision alerts, and the resulting operational data feeds Omniverse-based digital twins for merchandising and layout optimization.
98% neutral-to-positive customer reactions achieved with Mylow, Lowe’s AI-powered home improvement virtual advisor
Lowe’s built physically accurate digital twins of all 1,750+ stores in its network.
Mylow uses a hybrid approach ... combining OpenAI commercial models fine-tuned on Lowe’s proprietary data. NVIDIA NeMo Guardrails ensure protected and reliable AI-generated responses.
Store cameras automatically notify the nearest associate when customers dwell in aisles without support, enabling proactive assistance.
This process transforms 2D product images into precise, high-quality 3D models within minutes—at a cost of less than $1 per model.
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Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
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