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Build, Evaluate and Deploy a RAG-Based Retail Copilot with Azure AI: Cedric Vidal and David Smith
Feb 6, 2025 · 1:57:58
David Smith, Cedric Vidal, and Miguel Martinez lead a hands-on workshop on building a production-level RAG-based retail copilot using Azure AI. They demonstrate how to build a chatbot backend that retrieves product information from Azure AI Search via vector embeddings and customer history from Cosmos DB, then augments the LLM prompt to generate grounded answers. The session covers using Azure AI Studio and Prompt flow to orchestrate the RAG workflow, deploying the flow as a managed endpoint, and evaluating quality with GPT-4 as a judge on metrics like relevance and groundedness. The speakers also explain the LLM Ops lifecycle for iterative improvement and compare Prompt flow with Semantic Kernel and AutoGen.

Accelerate your AI journey with Azure AI model catalog: Sharmila Chokalingam
Feb 6, 2025 · 23:14
Shubhi and Sharmila present the Azure AI model catalog as a platform offering over 1,600 models including GPT-4, Mistral, Llama, Cohere, and Phi3, with a standardized inference API enabling easy model swapping. They demonstrate deployment via serverless API (pay-per-token) and managed compute, emphasizing that customer prompts and completions are not shared with model providers or used for training. The platform includes model benchmarks, playground for RAG, and Prompt Flow for building generative AI apps with evaluation and variant comparison. Customer success stories include EY's EYQ chat adopted by 275,000 employees, CMA CGM's reduced response latency using Mistral, and Bridgestone's 30% reduction in forecasting errors with Nixtla's TimeGen.
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