Neo4j Announces Collaboration with Microsoft to Advance GenAI and Data Solutions

Neo4j native integrations with Microsoft Fabric and Microsoft Azure OpenAI Service unify data management, improve accuracy and reduce hallucination in AI applications

SAN MATEO, CALIF.  – Mar 26, 2024 – Neo4j®, a Graph Database and Analytics leader, announced a collaboration with Microsoft to deliver a unified data offering that addresses customers’ critical data needs for Generative AI (GenAI). Specifically, the collaboration will see Neo4j’s powerful graph capabilities natively integrated into Microsoft Fabric and Microsoft Azure OpenAI Service to seamlessly combine structured and unstructured data, and enable customers to uncover hidden patterns and relationships within their data for better insights and decision-making, all as part of a comprehensive solution.

“By 2025, graph technologies will be used in 80% of data and analytics innovations — up from 10% in 2021 — facilitating rapid decision-making across the enterprise,” predicts Gartner® in its Emerging Tech Impact Radar: Data and Analytics November 20, 2023 report. 1Gartner also notes, “The ability to discover and document data use cases and help build knowledge graphs out of data uses is becoming a vital capability. It is the first step to resolving fragmented data management issues by enabling a GenAI-augmented data fabric,” in its January 23, 2024 report titled Innovation Insight: How Generative AI is Transforming Data Management Solutions.

Azure OpenAI Service enables businesses to use advanced AI models and tools that unlock the full potential of their data. Microsoft Fabric is an AI-powered analytics platform that enables everything from data movement to data science, real-time analytics, and business intelligence. Customers benefit from the integration of Neo4j’s graph database within Azure OpenAI and Microsoft Fabric in the following ways:

  1. Transform unstructured data into knowledge graph: Developers can use OpenAI Service to process unstructured data, structure it, and load it into a knowledge graph. Once in a knowledge graph, users extract insights leveraging Neo4j data visualization and query tools like Bloom or use Neo4j connector with Power BI for business intelligence (BI). 

  2. Enhance contextual understanding and explainability with GraphRAG: With Neo4j’s GenAI functions, Azure OpenAI Service can be used for fully integrated GraphRAG applications, whereby LLM queries can be used against enterprise data in knowledge graphs. GraphRAG is an enhanced form of Retrieval Augmentation Generation (RAG) whose results demonstrate intelligence or mastery that outperforms other approaches previously applied to private datasets. Enterprises can also use Gen AI orchestration platforms like LangChain and LlamaIndex to build intelligent GenAI applications.  

  3. Long-term memory for LLMs with vector embedding integration: Neo4j provides long-term memory for large language models by supporting native vector embeddings. Neo4j has inbuilt support for vector storage and search capability for intelligent GenAI applications. Developers can now natively use Azure OpenAI embedding APIs to create embeddings and store them in the Neo4j Database.

  4. Graph-powered insights as part of Microsoft Fabric unified data platform: Microsoft Fabric customers can now use Neo4j Graph Database and Analytics capabilities to discover hidden patterns and relationships deeply, easily, and quickly. Developers can implement Azure Data Factory to ingest data from OneLake into Neo4j, extract data from Synapse Data Warehouse using the Neo4j data warehouse connector, run Graph Data Science algorithms from Synapse Data Science Notebooks, and leverage Power BI to build interactive dashboards on Neo4j Knowledge Graphs.

  5. Graph Analytics as native Fabric workload: Neo4j and Microsoft Fabric teams are working together to deliver Neo4j as a native workload for Graph Analytics on Microsoft Fabric platform. This will enable users to access graph analytics workload directly from the Microsoft Fabric console, create Graph models from OneLake data, analyze Graph data, run Graph Data Science Algorithms using Neo4j Bloom, and write back results into OneLake for a seamless end-to-end integration.  

Neo4j’s Azure OpenAI Service integration is generally available now. The integration of Neo4j’s graph database into Microsoft Fabric will be generally available later this year. 

Neo4j also announced the general availability of Neo4j’s fully managed graph database offering AuraDB on Azure Marketplace, giving developers a frictionless, fast-start experience on generative AI. Azure Marketplace offers thousands of industry-leading software and services that are certified and optimized on Azure.

For more information about Neo4j’s collaboration with Microsoft, read our blog post or visit the Neo4j booth #307 at Microsoft FabCon, March 26-28.

Supporting quotes

Srinivas Suravarapu, CEO, ScribeStar

“ScribeStar is on a mission to make capital markets cheaper and easier to access by providing technology that helps companies list, report, and fulfill ongoing obligations. Today’s announcement underscores how our partners, Microsoft and Neo4j, enable SaaS businesses like ScribeStar to provide powerful solutions to discover complex relationships within our data. The ability to build intelligence with speed and precision using graphs is integral to developing the next generation of intelligent solutions in capital markets. Graphs are everywhere, and so is the cloud – a future of analytics powered by Microsoft Fabric and Neo4j is inevitable, and this partnership makes absolute sense for ISVs like us."

Sudhir Hasbe, Chief Product Officer, Neo4j

"We’re excited to combine Neo4j’s unparalleled graph capabilities alongside Microsoft’s seamless scalability, advanced AI capabilities of Azure OpenAI, and AI Powered Analytics Platform with Microsoft Fabric. Enterprises can now unlock deeper insights, navigate complex data relationships, and drive better decision-making and innovation in ways that were not possible before. Together, we’re helping customers redefine what’s possible for their data in an increasingly interconnected GenAI world.”

Arun Ulag, CVP, Azure Data, Microsoft

"Microsoft is committed to empowering organizations with the tools and technologies they need to thrive in today’s data-driven world," said Arun Ulag, CVP, Azure Data, Microsoft. "Our collaboration with Neo4j represents a significant step forward in delivering innovative data solutions that will enable businesses to unlock new opportunities and drive digital transformation in the GenAI era."

Neo4j Microsoft Fabric Collaboration

Supporting visual / diagram caption (above): A common reference architecture for applying Generative AI with knowledge graphs using Microsoft Azure Open AI Service and Neo4j.

1GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.

About Microsoft

Microsoft (Nasdaq “MSFT” @microsoft) enables digital transformation for the era of an intelligent cloud and an intelligent edge. Its mission is to empower every person and every organization on the planet to achieve more.

About Neo4j

Neo4j, the Graph Database & Analytics leader, helps organizations find hidden relationships and patterns across billions of data connections deeply, easily and quickly. Customers leverage the structure of their connected data to reveal new ways of solving their most pressing business problems, from fraud detection, customer 360, knowledge graphs, supply chain, personalization, IoT, network management, and more – even as their data grows. Neo4j’s full graph stack delivers powerful native graph storage with native vector search capability, data science, advanced analytics, and visualization, with enterprise-grade security controls, scalable architecture and ACID compliance. Neo4j’s dynamic open-source community brings together over 250,000 developers, data scientists, and architects across hundreds of Fortune 500 companies, government agencies and NGOs. Visit neo4j.com.

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