While RAG is the go-to solution for enterprise search, retrieving relevant data from trusted sources as a ground for its answers, GraphRAG can enhance the relevance and quality of agentic retrieval by using a knowledge graph to retrieve structured, interconnected data rather than just isolated chunks of text.

Business Challenge:

In this real-life case study, a large retail organization has been facing a challenge to keep its inhouse processes compliant with EU CBAM regulations. EU CBAM regulations are prone to change frequently and the manual struggle to enable compliance across a wide range of nested processes has been real. Understanding the complexity of this challenge, IT team has been keen on enabling the inhouse sustainability team with the option of using an intelligent context-aware agent that can not only answer relevant questions, but it also takes agency to evaluate the current state of the inhouse processes in accordance to the latest EU regulatory changes, identifying any misalignment and proposing valid adjustments for better EU compliance.

Solution based on Azure multi-agent architecture:

By leveraging GraphRAG based on a custom Azure knowledge graph and multi-agent concurrent agent architecture, a custom Azure EU sustainability agent is developed to support the process of EU CBAM compliance inside the organization.

Join this compelling session to learn about:

-Azure Knowledge Graphs and GraphRAG: their ability to answer global queries that address the entire dataset,

-Azure multi-agent architecture in action, and the importance choice of orchestration

Assumed Knowledge:

– Be familiar with RAG, Have interest in muti-agent architecture

Practical Takeaways:

A comparison of RAG vs Graph RAG, Azure Knowledge Graphs and GraphRAG: their ability to answer global queries that address the entire dataset, Azure multi-agent architecture in action, and the importance choice of orchestration

Out of Session Scope:

We will not build a knowledge graph