Neo4j and Amazon Web Services (AWS) have inked a multi-year Strategic Collaboration Agreement (SCA) that will allow businesses to improve generative artificial intelligence (AI) results by combining knowledge graphs and native vector search in a way that lessens generative AI hallucinations and improves results’ accuracy, transparency, and explanation. For developers who require long-term memory for large language Models (LLMs) based on their unique company data and domains, this helps resolve a frequent issue.

Additionally, Neo4j announced that Neo4j Aura Professional is now generally available on the AWS Marketplace, giving developers a seamless, quick start with generative AI. Software that runs on AWS can be easily found, tested, purchased, and deployed with ease with the help of AWS Marketplace, a digital library that features thousands of listings from independent software suppliers.

Leading graph database Neo4j has an inbuilt vector search that can identify patterns and relationships, both explicit and implicit. Neo4j also builds knowledge graphs, facilitating effective reasoning, inference, and retrieval of pertinent data by AI systems. Neo4j’s features allow it to function as both an enterprise database and a long-term memory for generative AI systems such as LLMs, allowing them to produce outcomes that are more visible, explainable, and accurate.

“The combination of knowledge graphs by Neo4j and generative AI capabilities by Amazon Bedrock will allow us to build generative AI applications at scale and democratize credit analysis and insights for our market,” stated Pablo Lima, CEO of TAG Infraestrutura do Mercado Financeiro. “Neo4j is the ideal database to store these highly connected transactions more effectively and respond more quickly to new rules. We have all kinds of data from transactions, including merchants, creditors, locations, processing devices, transaction nature, amounts, values, and more. Neo4j’s algorithms and analytical tools also assist us in developing new solutions that give our partners information on how to better customize their goods and services for creditors and merchants.”

Harrison Chase, CEO, LangChain, added, “LangChain with Neo4j and Amazon Bedrock can now work together using Retrieval Augmented Generation (RAG) to create virtual assistants that are grounded in enterprise knowledge, removing hallucinations and providing more accurate, transparent, and explainable results. It’s a great step forward in helping teams close the gap between the magical user experience that generative AI enables and the work it requires to get there.”

Atul Deo, General Manager, Amazon Bedrock, AWS, maintained, “At AWS, we remain committed to empowering organisations with a diversity of tools and resources to build generative AI solutions that align with their unique customer experiences, applications, and business requirements. With Neo4j’s graph database and Amazon Bedrock’s integration, we aim to provide customers sophisticated options to deliver more accurate, transparent, and personalised experiences for their end-users in a fully managed manner.”

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Sudhir Hasbe, Chief Product Officer, Neo4j, said, “Neo4j has been an AWS Partner since 2013 – with this latest collaboration representing an essential union of graph technology and cloud computing excellence in a new era of AI. Together, we empower enterprises seeking to leverage generative AI to innovate better, provide the best outcome for their customers, and unlock the true power of their connected data at unprecedented speed.”

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