Agentic AI Platform for Global Retail Contact Centre Operations
Reimagining retail customer support with conversational commerce, real-time agent intelligence, and AI-driven operational automation.
Client
A leading global fashion retailer managing high-volume e-commerce and customer support operations across multiple regions.
Problem Statement
Scaling consistent, high-quality customer support across global retail operations while reducing agent workload and service friction.
Industry
Quick Summary
- Delivered an AI-powered conversational commerce assistant and an agentic contact centre intelligence platform for global retail operations.
- Enabled real-time agent guidance, automated after-call workflows, intelligent routing, and knowledge-grounded customer interactions across voice, chat, and messaging channels.
- Reduced after-call documentation effort by 40–60% while improving response consistency, handling efficiency, and customer satisfaction.
- Currently being rolled out across 26 countries, with multiple regions already fully operational.
Client Profile
The client is a leading Japanese global fashion retailer operating large-scale e-commerce and customer support operations across multiple international markets. Managing high volumes of product enquiries, order support, returns, and customer engagement interactions, the retailer required scalable AI-driven capabilities to improve operational efficiency and deliver consistent customer experiences across regions.
Challenges: Scaling Retail Customer Support
The retailer’s support teams managed thousands of daily interactions spanning product discovery, sizing guidance, order management, returns, shipping, and inventory enquiries. As customer expectations increased across digital channels, operational complexity began impacting both service quality and agent efficiency.
Key challenges included:
- Limited customer self-service capabilities for sizing, product fit, availability, and purchase-related enquiries.
- High cart abandonment caused by unresolved customer questions during the buying journey.
- Lack of scalable personalization mechanisms at critical purchase decision points.
- Agents required to navigate multiple disconnected systems during live customer interactions.
- Inconsistent response quality across agents, channels, and geographies.
- Manual after-call documentation reducing agent productivity and throughput.
- Extensive onboarding and training requirements due to product catalog complexity and seasonal changes.
Solution: Agentic AI Platform for Conversational Commerce and Contact Centre Intelligence
We designed and implemented two interconnected AI-powered solutions that transformed both customer-facing commerce experiences and internal contact centre operations.
The platform combined conversational AI, agentic orchestration, intelligent knowledge grounding, and operational automation to create a unified retail support ecosystem capable of scaling across regions and channels.
Conversational AI Assistant
An AI-powered conversational assistant was embedded directly into the retailer’s e-commerce ecosystem to guide customers from product discovery through completed purchase.
Using natural language understanding and contextual customer intelligence, the assistant delivered conversational experiences aligned with the retailer’s brand voice while reducing friction throughout the shopping journey.
Key capabilities included:
- Conversational handling of product enquiries, order tracking, shipping updates, and customer support requests.
- Personalized product recommendations based on browsing behavior and purchase history.
- Integrated payment processing, order confirmation, and shipment tracking workflows.
- Real-time integration with e-commerce and inventory management platforms.
- Intelligent escalation of sensitive or complex queries to live agents based on skill alignment and workload availability.
Agentic Contact Centre Engine
We also deployed an agentic orchestration layer across the retailer’s live support operations spanning voice, chat, and messaging channels.
The system continuously intercepted and analyzed live customer interactions in real time, automatically surfacing contextual guidance, customer information, and operational recommendations directly within the agent workflow.
This eliminated the need for agents to manually search across disconnected systems during live interactions.
Key capabilities included:
- Real-time next-best-action recommendations during live customer engagements.
- Automatic retrieval of customer profiles, order history, and policy information.
- Sentiment analysis and priority-based escalation detection for high-risk interactions.
- Knowledge-grounded assistance powered through an intelligent knowledge pipeline.
- Automated call summarization, interaction tagging, and case-note generation after every interaction.
- Automated ticket updates and resolution draft generation to reduce after-call work.
- Multi-LLM orchestration designed to optimize response speed, accuracy, and operational cost.
- AI governance controls including PII masking, safety enforcement, and audit logging.
Scalable AI and Cloud Architecture
The platform leveraged a modern AI and cloud-native architecture designed for enterprise-scale retail operations.
The solution incorporated:
- Multi-LLM orchestration across leading AI models.
- Agentic AI workflows powered by cloud-based AI infrastructure.
- Real-time orchestration and workflow management services.
- Enterprise-grade integrations with commerce, inventory, customer support, and operational systems.
- Distributed analytics and operational intelligence pipelines for live interaction processing.
Technical Highlights
- Agentic orchestration layer for real-time contact centre intelligence.
- Conversational AI assistant integrated into the digital commerce journey.
- Multi-LLM orchestration balancing speed, accuracy, and operational cost.
- Real-time sentiment analysis and escalation-aware routing.
- Automated after-call summarization and case-note generation.
- Intelligent knowledge grounding for policy-aligned responses.
- Enterprise-grade governance with PII masking and audit logging.
- Integration with e-commerce, inventory, and customer support systems.
- Omnichannel support across voice, chat, and messaging platforms.
Impact
- Reduced after-call documentation effort by 40–60% through AI-driven summarization and workflow automation.
- Expanded rollout across 26 countries, with multiple regions already fully operational.
- Improved average handling efficiency by eliminating manual information retrieval during live interactions.
- Increased customer satisfaction through faster issue resolution and more consistent service quality.
- Standardized policy-aligned responses across agents, channels, and geographies.
- Reduced onboarding effort for new agents through real-time in-call guidance and contextual assistance.
Client Profile
Challenges
QBurst Solution
Technical Highlights
Impact
