A year ago, Neo4j announced a Strategic Collaboration Agreement with Amazon Web Services (AWS) to accelerate enterprise GenAI development and resolve key AI challenges, including LLM hallucination. We previously achieved AWS Competency Partner Status in Data and Analytics—and we’re thrilled to share that we’ve earned AWS competencies in four additional areas: AWS Financial Services, AWS Automotive, AWS Generative Artificial Intelligence, and AWS Machine Learning.
The new competencies reflect our commitment to helping customers solve industry-specific challenges with graph-based solutions—solutions that can provide a powerful competitive advantage. “By 2025,” Gartner notes in a recent report, “graph technologies will be used in 80% of data and analytics innovations, up from 10% in 2021, facilitating rapid decision-making across the enterprise.”
Customers can now seamlessly integrate graph data models into diverse AWS workflows, enabling faster deployment, more accurate predictions, and deeper insights.
New Competencies Address Industry-Specific Challenges
AWS’s rigorous review process validated the Neo4j product, best practices, and customer references, ensuring businesses can trust Neo4j to meet critical industry-specific needs. Only a select few ISVs obtain AWS competency status, and fewer still obtain as many as Neo4j has. Here’s a quick overview of the new competencies and the challenges they help organizations overcome.
AWS Financial Services Competency
This competency recognizes Neo4j for providing deep expertise that helps organizations manage critical industry issues such as risk management, core systems implementations, and data management. One of only 139 Financial Services Competency partners, Neo4j has extensive experience helping the financial services industry address its most daunting challenges, including fraud detection and prevention. Neo4j’s AWS-supported reference architecture for fraud ring detection makes it easy to implement Neo4j in AWS environments, enabling institutions to connect diverse data points—transactions and behavioral patterns, for example—and uncover suspicious activities in real time. To receive this designation, AWS Partner Network (APN) members must possess deep AWS expertise and undergo security, reliability, and performance assessments. With Neo4j and AWS, firms can ensure regulatory compliance while improving their security posture.
AWS Automotive Competency
As the automotive industry continues to evolve, Neo4j graph technology helps automakers understand the complex relationships between parts, sensors, and systems, allowing them to optimize everything from production lines to in-vehicle features. Manufacturers can use graph to drive faster innovation cycles, enhance supply chain efficiency, and improve vehicle safety. The AWS Automotive Competency differentiates Neo4j as an APN member with demonstrated technical proficiency and proven customer success in running cloud solutions on AWS for the automotive industry. Neo4j is one of only 31 Automotive Competency partners. To receive the designation, Neo4j underwent rigorous technical validation and provided customer references.
AWS Generative Artificial Intelligence Competency
This designation recognizes Neo4j as an AWS Partner that helps customers drive the advancement of services, tools, and infrastructure pivotal for implementing generative AI technologies. Neo4j is one of only 171 Generative AI Competency partners. Graph technology allows organizations to manage the vast, interconnected datasets that GenAI apps require to produce accurate, transparent, and explainable results. Central to this effort is GraphRAG, which combines knowledge graphs and retrieval-augmented generation (RAG). Neo4j’s AWS-approved reference architecture helps customers implement GraphRAG and other graph solutions for GenAI.
AWS Machine Learning Competency
The AWS ML Competency differentiates Neo4j as an APN member that helps organizations solve data challenges and enable ML and data science workflows or offers SaaS/API-based capabilities that enhance end applications with machine intelligence. Neo4j is one of only 100 ML Competency partners. Integrating graph technology with AWS machine learning capabilities allows customers to build highly accurate ML models that detect complex patterns and relationships. This can dramatically improve decision-making and operational efficiency across industries. Use cases include predictive analytics, customer segmentation, dynamic pricing, recommendation systems, churn prediction, and predictive maintenance. Neo4j attained the AWS ML Competency by demonstrating validated expertise and ML experience on AWS.
New Integrations Offer Secure, Seamless Experiences on AWS
In addition to its Competencies, Neo4j will focus on four new initiatives to streamline Neo4j adoption for AWS customers:
1. AWS Seller Prime
Our participation in the AWS Seller Prime Program simplifies the experience of getting started with Neo4j on AWS. Seller Prime makes it easier to learn about Neo4j and graph databases on AWS and discover if Neo4j is the right fit for your use case. As part of this effort, we’re improving our free trial and Pay as You Go experiences.
2. Buy With AWS
Buy with AWS integration simplifies the purchase of Neo4j through the AWS Marketplace. Our initial integration simplifies the purchase of Neo4j AuraDB Professional through the Neo4j Deployment Center. We’re also exploring integrating Buy with AWS directly into the Neo4j AuraDB console. This will make it easier for customers to change AuraDB product tiers using AWS Marketplace payment mechanisms.
3. VPC Resources Through AWS PrivateLink and VPC Lattice
VPC Resources through AWS PrivateLink and VPC Lattice is a new feature from the AWS PrivateLink team. It simplifies the usage of PrivateLink with ISV software while adding support for VPC Lattice. The initial integration demonstrates how an application running in Lambda can securely access a Neo4j EE instance on AWS EKS. This lays the groundwork for further integration with Neo4j AuraDB which can dramatically simplify user interaction with PrivateLink.
4. Import and Export Data Using Neo4j and Glue 5
With the launch of Glue 5, JDK 17 is now supported, enabling the use of the Neo4j JDBC driver with Glue. Customers can use Glue to move data in and out of Neo4j more easily, simplifying connectivity to common AWS services like Redshift, EMR, and RDS. Customers can also build graphs from the data in their existing AWS estate more easily while enriching their AWS data systems with graph information.
Cultivating a Customer-Focused Partnership
The needs of our customers have always shaped our partnership with AWS. AWS-validated competencies and reference architectures allow you to solve complex data challenges in finance, automotive, ML, GenAI, and more. We’ve made it easier than ever to deploy graph-based solutions tailored to specific needs—and we’re committed to deepening our AWS partnership even further.
If you’re ready to innovate with Neo4j on AWS, take a look at our solutions on AWS Marketplace, or email us at ecosystem@neo4j.com to speak to a graph expert today.
For more information on how Neo4j and AWS drive innovation together, visit neo4j.com/partners/amazon/.
