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Merge pull request #347 from zach-blumenfeld/fix-spelling-grammer
Fixing Grammar & Typos
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modules/genai-ecosystem/pages/customer-graph-agent.adoc

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= GraphRAG Agent for \Customer & Retail Analytics
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= GraphRAG Agent for Customer & Retail Analytics
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include::_graphacademy_llm.adoc[]
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:slug: customer-graph-agent
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:author: Zach Blumenfeld
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This is an *end-to-end worked example for building a GraphRAG agent to accelerate customer and retail analytics*. It covers the entire process from:
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1. *Quickly constructing a graph from mixed unstructured and structured data sources*.
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2. *Resolving and linking entities* in the graph along the way.
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3. *Creating diverse graph retrieval tools*, including query templates, vector search, dynamic text2Cypher, and graph community detection to answer a boarder range of questions.
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4. *Building an agent* with Semantic Kernel for conducting analytics and responding to complex user questions.
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1. *Quickly constructing a graph from mixed unstructured and structured data sources*
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2. *Resolving and linking entities* in the graph along the way
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3. *Creating diverse graph retrieval tools*, including query templates, vector search, dynamic text2Cypher, and graph community detection to answer a boarder range of questions
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4. *Building an agent* with Semantic Kernel for conducting analytics and responding to complex user questions
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All of this using a central *source-of-truth graph schema* to govern the process and AI-interactions, ensuring higher data & retrieval quality.
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Follow the instructions below to try it yourself! 🚀
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image::ai-customer-graph-query-sample.png[align=center]
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image::ai-customer-graph-query-sample.png[align="center"]
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== Prerequisites
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Once complete, you can check the database to see the generated graph. Go to the https://console.neo4j.io/[Aura Console^] and navigate to the Query tab.
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image::ai-customer-graph-unstruct-ingest-1-goto-query.png[align=left]
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image::ai-customer-graph-unstruct-ingest-1-goto-query.png[align="left"]
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Select the "Connect instance" button
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