AI is changing the way we think about databases. You can’t have reliable AI agents without reliable data infrastructure.

The database is no longer just where data lives, but where context gets assembled – and in AI, context is everything.

According to @godofprompt, leading AI engineers at OpenAI, Anthropic, and Microsoft are shifting from traditional RAG (Retrieval-Augmented Generation) systems to ...

According to God of Prompt on Twitter, Graph Retrieval-Augmented Generation (Graph RAG) enables relationship traversal by connecting customer tickets, API documentation, engineering discussions, and ...

1 Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing, China 2 Key Laboratory of Agricultural Blockchain Application, Ministry of Agriculture and Rural Affairs, ...

Organizations dealing with regulatory compliance and contract management face challenges: ...

Abstract: This paper presents a secure question answering framework for financial compliance using a graph-based retrieval-augmented generation (Graph-RAG) model. The system constructs a multi-layer ...

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GraphRAG (Graphs + Retrieval Augmented Generation) is a technique for richly understanding text datasets by combining text extraction, network analysis, and LLM prompting and summarization into a ...

This guide explains what Microsoft Graph Explorer does and how you can use it to test Microsoft Graph API requests quickly. You will learn how to open it, run queries, adjust permissions, view code ...

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