AI-Based Retail Customer Journey Agent

This project presents a robust and scalable omni-channel sales solution utilizing an Agentic AI Framework built upon a Large Language Model (LLM). By leveraging modern agentic principles, the system features a central “Sales Agent” that tokenizes customer intent and orchestrates multiple specialized “Worker Agents” to handle tasks such as inventory checks, recommendations, and payment processing. The use of a coordinated, multi-agent architecture ensures a seamless, human-like conversational journey while maintaining context across channels, making it suitable for real-time retail applications. The framework offers a practical solution to combat fragmented customer experiences, a rising concern in today’s digital-first retail age. It can be integrated into web chats, mobile apps, and in-store kiosks, aiding sales teams, e-commerce platforms, and customer support in increasing Average Order Value (AOV) and boosting conversion rates.