Retail & E-Commerce – Europe | AI-Driven Product Recommendation (RAG-Based)

AI-Powered Conversational Product Assistant

SilwaTech implemented a conversational AI assistant enabling customers to:

• Describe fishing conditions, target species, or equipment preferences
• Receive contextual product suggestions tailored to their needs
• Ask follow-up questions for refined recommendations
• Navigate product categories more intuitively

Retrieval-Augmented Generation (RAG) Architecture

To ensure recommendations were accurate and inventory-aware:

• Product data was indexed in a vector database
• Semantic embeddings were generated for product descriptions
• User queries were matched against contextual product knowledge
• GPT-4 generated structured, explainable recommendations
• Live Magento data ensured real-time inventory alignment

This approach prevented hallucinated responses and grounded outputs in actual product availability.

Magento Integration

The AI assistant was fully integrated into the Magento platform:

• Direct product linking within chat responses
• API-driven inventory validation
• Seamless frontend embedding within the store experience
• Scalable backend services to handle peak traffic

Performance & Scalability

• Optimized inference pipeline for responsive customer interaction
• Cloud-native deployment supporting scaling during seasonal demand
• Logging and monitoring for performance insights

• Improved product discovery through conversational interaction
• Increased engagement with contextual, expert-level guidance
• Reduced reliance on manual customer support
• Higher customer confidence in purchasing decisions
• Scalable AI architecture supporting future expansion