Deliver production-ready AI search on unstructured data with RAG | ODSP925

Author: Microsoft Developer - Bewertung: 1x - Views:16

RAG is easy to prototype but difficult to run in production. This session shows how to move from proof of concept to production-ready AI search on unstructured data. Build a simple RAG pipeline, then explore patterns for scaling with agentic RAG, graph-based retrieval, and entity recognition. Learn how to choose the right approach for performance, relevance, and maintainability from real-world examples.



𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻:

This is one of many sessions from the Microsoft Build 2026 event. View even more sessions on-demand and learn about Microsoft Build at https://build.microsoft.com



ODSP925 | English (US) | Agents & apps





Pre-recorded | (100) Foundational





#MSBuild



Chapters:

0:00 - Why retrieval augmented generation is important today

00:01:59 - Definition of context augmented generation and examples from YouTube Gemini

00:04:26 - Data Ingestion and Vector Embeddings in RAG

00:05:27 - Complexity of End-to-End RAG Architecture

00:07:59 - Rapid Search Experience Creation with HTML Widget Builder

00:08:32 - Demo: Building a Financial Dashboard with .NET and Blazor

00:11:33 - Using the C# SDK and Blazor for Custom Interfaces

00:12:54 - Displaying Data with Telerik UI for Blazor

00:13:55 - Closing and Accessing Additional Resources