Conversational Search for E-Commerce Marketplace

DCube developed a conversational search and data retrieval system for Fabric Inc.'s e-commerce marketplace, enabling users to find relevant products and pages using natural language queries. The solution leverages an OpenAI-powered LLM to interpret user intent and dynamically construct backend API requests for accurate and contextual results.

The Client

Client Name: Fabric Inc.

Industry: Retail

Region: US

Company Size: Enterprise

The Challenge

Keyword-based search and static filters limit user experience on large e-commerce platforms with extensive product catalogs. Users often express complex intent in natural language, while backend systems require structured queries to retrieve precise and relevant data efficiently.

The Solution

DCube implemented a conversational AI layer powered by an OpenAI LLM to analyze user queries, infer intent, extract constraints, and translate them into structured API requests compatible with Fabric's backend services. This approach bridged the gap between human language and machine-readable search APIs, significantly improving discovery and relevance.

Key Features

• OpenAI LLM–powered natural language understanding
• Intent detection and constraint extraction from user queries
• Dynamic API request generation for backend data retrieval
• Intelligent filtering of products and marketplace content
• Seamless integration with existing e-commerce infrastructure

Technologies Used

• OpenAI Large Language Models (LLMs)
• Natural Language Processing (NLP)
• Python

Results & Impact

• Improved relevance and accuracy of search results
• Reduced friction in product discovery and navigation
• Enhanced user engagement through conversational interaction
• Increased likelihood of conversion from search sessions
• Scalable foundation for future AI-driven personalization and recommendations

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