Global Footwear Brand

A multi-agent shopping and support experience across two brands

This global footwear company replaced a legacy chatbot with context-aware agents for product discovery, order tracking, and live-agent handoff across 14+ regions.

Date
August 7, 2026
Topic
AI Agents
Summary

This footwear company ran a legacy chatbot across two global brands, with limited self-service and no intelligent product discovery, while moving to headless commerce. We built a shopper agent for guided discovery with neural search and a support agent for order tracking, returns and escalation, both grounded in the knowledge base. One agent architecture now serves both brands across 14+ regions without adding to live-agent load.

Focus Areas
AI shopper agent, AI support agent, Neural product search
Challenge

The company ran a legacy chatbot across two global brands, with limited self-service and no intelligent product discovery. High inbound volume, a fragmented bot-to-agent handoff, and a shift to headless commerce meant any new build had to work across storefronts, languages, and 14+ regions - without adding to live-agent load.

Solution

We built a multi-agent experience: a shopper agent for guided product discovery with neural search, and a support agent for order tracking, returns, and escalation. The work spanned order-status and return integration with the order-management system, the escalation flow, headless front-end deployment, and knowledge-base grounding for accurate answers.

Results
2
consumer brands served from one agent architecture
14+
global regions in scope
>73%
legacy chatbot containment rate to beat