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Retail GenAI copilot

Retail · GenAI

Shipped a retrieval-augmented service assistant across 4 languages with policy guardrails within 8 weeks.

Key Result

300+ support hours saved monthly

Duration

8 weeks

Team

2 engineers + 1 ML specialist

Technologies

6 tools

The Challenge

A global retail company with operations in 12 countries was drowning in customer support tickets. Their support team was handling 50,000+ queries monthly, with significant portions being repetitive questions about return policies, store locations, and product availability. They needed a solution that could handle multiple languages while respecting regional policy differences.

Our Solution

We built a RAG-powered customer service assistant that ingests their knowledge base, policy documents, and real-time inventory data. The system uses semantic search to find relevant context and generates responses with built-in guardrails to prevent hallucinations and ensure policy compliance. We implemented language detection and region-specific policy routing, with a human escalation path for complex queries.

Results & Outcomes

  • 300+ support hours saved monthly through automated first-line response
  • 85% of routine queries handled without human intervention
  • Support across English, Spanish, French, and German
  • Average response time reduced from 4 hours to 30 seconds
  • Customer satisfaction scores improved by 18%

Technologies Used

OpenAI GPT-4LangChainPineconeNext.jsAWS LambdaCloudFront
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