1. Introduction: Explore how AI & ML, integrated with Microsoft Fabric, can transform customer experiences on e-commerce platforms.
2. Customer and Product Profiling: Demonstrate profiling customers and products in Power BI, utilizing data from Microsoft Fabric's OneLake, to derive actionable insights.
3. Building a Recommender Engine: Show how to leverage these insights to transform a Large Language Model (LLM) into an effective product recommendation engine, aimed at boosting basket sizes and sales performance.
4. Interactive Chatbot Creation: Illustrate the development of a chatbot using Azure AI Studio, capable of handling product inquiries and customer complaints, by accessing the OneLake's extensive product database and historical order data.
5. Enhancing Chatbot Responses: Detail the process of utilizing Microsoft Fabric’s notebooks for improving chatbot interactions, emphasizing on analysis, comparison, and scoring of chatbot responses against human interactions, with help from prompt flow.
6. Data-Driven Decisions: Highlight how to use the insights gathered from the chatbot and recommendation engine to inform business strategies.
7. Visualizing Impact: Showcase the integration of these AI models with real-time data visualization tools in Microsoft Fabric, emphasizing their effect on customer engagement and sales trends.
8. Model Orchestration: Demonstrate the orchestration of these models in Microsoft Fabric for real-time inference, ensuring seamless and efficient operations.
9. Scalability and Collaboration Features: Discuss the scalability of Microsoft Fabric's AI & ML solutions and its collaborative environment for teams.
10. Q&A