Injecting Neo4j Graph Context into Microsoft Agent Framework: Neo4jContextProvider vs Tool Call
Master Neo4jContextProvider vs tool calls in Microsoft Agent Framework to build flexible, production-ready .NET GraphRAG architectures.

Explore the complete evolution of RAG from foundational setups to advanced, multi-hop reasoning and intelligent chunking.
Master Neo4jContextProvider vs tool calls in Microsoft Agent Framework to build flexible, production-ready .NET GraphRAG architectures.
Learn how to control RAG in Microsoft Agent Framework. Master AIContextProvider and TextSearchProvider for clean, production-ready .NET pipelines.
Learn how to master RAG Security in Azure AI Search using Document Level Access, userIds, groupIds, and rbacScope. Build enterprise-ready AI!
Understand how Foundry IQ uses Agentic Retrieval Pipeline to navigate data silos. Learn how to tune Reasoning Effort for speed and accuracy.
Learn how Foundry IQ uses Knowledge Bases and Knowledge Sources to simplify Agentic Retrieval. Build enterprise-ready RAG in Microsoft Foundry.
Discover Graph RAG with C# and Neo4j. Build a Knowledge Graph to improve AI accuracy and find deep connections.
Master Contextual Retrieval and enriched chunk logic with OpenAI and Azure AI Search. Use Prompt Caching in Microsoft Foundry to optimize RAG costs and speed.
Learn effective chunking strategies for RAG with C#, including Fixed-Size, Semantic, Hierarchical Parent-Child and more, shown in a real C# example.
HyDE for RAG explained: a practical guide to boosting retrieval accuracy with hypothetical answers and advanced search methods (Azure AI Search + Foundry).