Manual tagging couldn't keep pace with 30M products. Gemini now enriches the full catalog—67% faster, with richer detail for every listing.
An online home retailer carrying over 30 million products from more than 20,000 global suppliers, spanning every budget and style.
Manually tagging catalog attributes like color and style couldn't keep pace with continuous supplier onboarding, leaving new product listings...
“We want to take away the friction from our customers, but also look at ways that we can disrupt and supercharge what they used to do before. Generative AI and agentic capabilities allow us to take a fresh new look at what the process is and how we can optimize.”
E-commerce marketplace for furniture, home decor, and housewares.
Cloud computing services, AI infrastructure, and data analytics platforms for enterprises.
Wayfair's Product discovery is part of this use case:
Related implementations across industries and use cases
Manual reviews for artisan products took days. Gemini now generates listings from a single image, cutting approval to <1 hr.
Associates manually routed complex tickets and managed 47K product tags. Now, AI agents triage requests and classify attributes.
Fragmented vendor feeds obscured matching items. Now, AI pipelines parse millions of unstructured records into curated collections.
Sizing doubts held back shoppers. Virtual try-ons and a Gemini agent now visualize fit and answer queries, lifting conversion 2.6x.
In-store personalization and weekly ad creation were highly manual. Now, AI smart carts guide shoppers, and staff use agents to draft ads.
Workflows collapsed when staff changed roles. A meta-agent now turns plain-language descriptions into live agents—no AI team needed.
Elasticsearch kept every vector in RAM—cost-prohibitive at scale. One shared Milvus platform now runs 100+ workloads on 10B+ vectors.
Large AI training jobs meant fighting for preemptible slots or leaving campus. Marlowe gave any lab guaranteed multi-node access on demand.
Colleagues hunted through knowledge systems for answers; Global Markets hand-sorted emails before ops could act. Claude now handles both.
Manual tagging couldn't keep pace with 30M products. Gemini now enriches the full catalog—67% faster, with richer detail for every listing.
An online home retailer carrying over 30 million products from more than 20,000 global suppliers, spanning every budget and style.
Manually tagging catalog attributes like color and style couldn't keep pace with continuous supplier onboarding, leaving new product listings...
“We want to take away the friction from our customers, but also look at ways that we can disrupt and supercharge what they used to do before. Generative AI and agentic capabilities allow us to take a fresh new look at what the process is and how we can optimize.”
E-commerce marketplace for furniture, home decor, and housewares.
Cloud computing services, AI infrastructure, and data analytics platforms for enterprises.
Wayfair's Product discovery is part of this use case:
Related implementations across industries and use cases
Manual reviews for artisan products took days. Gemini now generates listings from a single image, cutting approval to <1 hr.
Associates manually routed complex tickets and managed 47K product tags. Now, AI agents triage requests and classify attributes.
Fragmented vendor feeds obscured matching items. Now, AI pipelines parse millions of unstructured records into curated collections.
Sizing doubts held back shoppers. Virtual try-ons and a Gemini agent now visualize fit and answer queries, lifting conversion 2.6x.
In-store personalization and weekly ad creation were highly manual. Now, AI smart carts guide shoppers, and staff use agents to draft ads.
Workflows collapsed when staff changed roles. A meta-agent now turns plain-language descriptions into live agents—no AI team needed.
Elasticsearch kept every vector in RAM—cost-prohibitive at scale. One shared Milvus platform now runs 100+ workloads on 10B+ vectors.
Large AI training jobs meant fighting for preemptible slots or leaving campus. Marlowe gave any lab guaranteed multi-node access on demand.
Colleagues hunted through knowledge systems for answers; Global Markets hand-sorted emails before ops could act. Claude now handles both.