RAG in C# & .NET 10: Build an Enterprise RAG App | Ep 1

RAG in C# and .NET 10: build an enterprise RAG application from scratch with Azure AI Search, Microsoft Foundry (Azure AI Foundry), Azure OpenAI and Angular. In Episode 1 you see the finished app answering questions from your own documents with citations, then set up the project. RAG (retrieval-augmented generation) lets an AI model answer from your own documents instead of guessing. In this RAG tutorial series we build a ChatGPT-style enterprise AI assistant that answers questions from YOUR company documents and images, with clickable citations. Everything is real: real Azure, real VS Code, line-by-line code, and the source pushed to GitHub at the end of every episode. In this episode: ✅ Live demo of the finished RAG app: streaming chat, AI image generation (tool calling), a document knowledge base with citations, follow-up questions and image search with a vision model ✅ Keyword vs vector vs hybrid search in Azure AI Search ✅ The tech stack and the three models in Microsoft Foundry (Azure AI Foundry): gpt-4.1-mini, text-embedding-3-small, gpt-image-1-mini ✅ RAG architecture: how Angular, the ASP.NET Core Web API, Azure Blob Storage, Foundry and Azure AI Search fit together ✅ Prerequisites ✅ Project setup in VS Code: README, .gitignore, git init, first commit and push to GitHub ⏱️ Chapters 00:00 What we build: enterprise RAG in C# 00:26 How this RAG course works 00:57 Live demo: the finished enterprise RAG app 01:21 General mode and streaming chat 01:46 AI image generation with tool calling 02:26 Uploading documents to the knowledge base 03:15 Asking questions with citations 03:59 Follow-up questions (query rewriting) 04:18 Keyword vs vector vs hybrid search 04:43 Image search with a vision model 05:29 The tech stack (.NET 10, Angular, Azure) 06:00 The models in Microsoft Foundry 06:26 RAG architecture explained 06:54 Prerequisites 07:15 Project setup in VS Code 07:56 README.md 08:22 .gitignore with dotnet new gitignore 08:38 git init and first commit 08:53 Push to GitHub 09:23 What's next in the series 📚 Enterprise RAG in .NET: the full course (watch in order) Ep 1 · RAG in C# & .NET 10: live demo, tech stack and project setup:    • RAG in C# & .NET 10: Build an Enterprise R...   Ep 2 · RAG explained: embeddings, chunking, vector and hybrid search:    • RAG Explained for Beginners: How It Works ...   Ep 3 · Azure AI Foundry (Microsoft Foundry) and Azure OpenAI model deployments:    • Azure AI Foundry Tutorial: Deploy GPT Mode...   Ep 4 · Azure AI Search and Blob Storage setup:    • Azure AI Search Tutorial for RAG: Service ...   Ep 5 · Web API backend and the first AI agent:    • Microsoft Agent Framework in C#: Your Firs...   Ep 6 · Knowledge ingestion: Blob Storage, indexer, skillset and vectorizer:    • Azure AI Search Indexer in C#: RAG Ingesti...   📦 Code for this episode: https://github.com/shahidnoor19/kodif... 📦 Full repository: https://github.com/shahidnoor19/kodif... ▶️ Full playlist:    • RAG in C# & .NET 10: Full Course (Azure AI...   ➡️ Next: Ep 2 · RAG explained in depth:    • RAG Explained for Beginners: How It Works ...   🧰 Stack: C# · .NET 10 · ASP.NET Core Web API · Angular · Microsoft Agent Framework · Microsoft Foundry / Azure AI Foundry · Azure OpenAI models · Azure AI Search · Azure Blob Storage 🔗 Connect GitHub: https://github.com/shahidnoor19 LinkedIn:   / shahid-noor-4563a6222   🔔 Subscribe to Kodify Dev for .NET, Azure, Angular and AI tutorials, and turn on notifications for the next episode. #RAG #dotnet #csharp #AzureAI #MicrosoftFoundry