Enterprise LLM infrastructure for one of the world's largest retailers—real-time personalization and AI-driven experiences at global catalog scale
Business Impact
$B+
Annual value generated
Product Coverage
400M+
Products in catalog
Global Scale
28
Countries served
Team Experience
4+ yrs
Global retail tech
A global retailer serves millions of customers daily across 28 countries with a catalog of 400M+ products. The challenge: how do you build AI products that deliver personalized, contextually relevant experiences at this unprecedented scale while maintaining responsible AI practices and driving measurable business impact?
We built a multi-tier GenAI platform leveraging LLMs for product understanding, customer intent recognition, and intelligent recommendations. The architecture includes: (1) Enterprise AI Gateway for model orchestration and responsible AI guardrails, (2) Real-time product intelligence layer processing catalog updates and customer signals, (3) Personalization engine delivering context-aware experiences across channels.
The platform generates $B+ in annual business value through improved customer experiences, operational efficiency, and new AI-powered capabilities. Key achievements include: Google Cloud GenAI Leader certification demonstrating enterprise-grade implementation, responsible AI framework balancing capability with ethical considerations, and scalable architecture serving global retail operations.
GenAI & LLM
Data Platform
Cloud & Scale
Product Analytics
Layer 1
AI Gateway
Model Orchestration
Responsible AI
Layer 2
Product Intelligence
Catalog + Signals
400M+ products
Layer 3
Personalization
Context-aware
Global scale
Having led multiple GenAI product launches, I've seen the real challenge isn't tech—it's bridging AI hype with business value. Focus on business-driven AI strategy, not technology for its own sake.
At hyperscale retail, responsible AI trade-offs aren't optional—they're core product requirements. Building practical frameworks for balancing AI capability with ethical considerations is essential for enterprise adoption.
Building AI products for global-scale retail means thinking in platforms, not features. Every AI capability must scale globally while maintaining local relevance across 28 countries.