MongoDB Announces Integration of MongoDB Atlas Vector Search with Amazon Bedrock to Power Next-Generation Applications on AWS

Rhea-AI Summary

MongoDB, Inc. (NASDAQ: MDB) announces integration of MongoDB Atlas Vector Search with Amazon Bedrock at AWS re:Invent 2023. The integration aims to facilitate the development of next-generation applications on Amazon Web Services, leveraging generative AI and semantic search capabilities.

Positive

• Integration with Amazon Bedrock opens up opportunities for developers to create highly engaging and customized end-user experiences.
• The use of operational data by MongoDB Atlas Vector Search simplifies the implementation of generative AI in applications, enhancing user experiences.
• The integration will enable developers to leverage proprietary data processed by MongoDB Atlas Vector Search to deliver up-to-date responses for a wide range of use cases.

Negative

• None.

New MongoDB Atlas Vector Search integration with Amazon Bedrock to help accelerate development of highly engaging applications powered by generative AI

Scalestack among customers excited to build next-generation applications using MongoDB Atlas Vector Search and Amazon Bedrock

LAS VEGAS, Nov. 29, 2023 /PRNewswire/ -- MongoDB, Inc. (NASDAQ: MDB) today at AWS re:Invent 2023 announced plans to integrate MongoDB Atlas Vector Search with Amazon Bedrock to enable organizations to build next-generation applications on Amazon Web Services (AWS) and their industry-leading cloud infrastructure. MongoDB Atlas Vector Search uses an organization's operational data to simplify bringing generative AI and semantic search capabilities into applications for highly engaging and customized end-user experiences. This integration will make it easier for developers to create applications on AWS that use generative AI to complete complex tasks for a wide range of use cases and deliver up-to-date responses based on proprietary data processed by MongoDB Atlas Vector Search. To learn more about building AI-powered applications on MongoDB Atlas, visit mongodb.com/use-cases/artificial-intelligence.

"Customers of all sizes from startups to enterprises tell us they want to take advantage of generative AI to build next-generation applications and future proof their businesses. However, many customers are concerned about ensuring the accuracy of the outputs from AI-powered systems while protecting their proprietary data," said Sahir Azam, Chief Product Officer at MongoDB. "With the integration of MongoDB Atlas Vector Search with Amazon Bedrock, we're making it easier for our joint-AWS customers to use a variety of foundation models hosted in their AWS environments to build generative AI applications that can securely use their proprietary data to improve accuracy and provide enhanced end-user experiences."

Amazon Bedrock is a fully managed service from AWS that offers a choice of high-performing foundation models (FMs) via a single API, along with a broad set of capabilities to build generative AI applications with security and privacy. This new integration with Amazon Bedrock allows organizations to quickly and easily deploy generative AI applications on AWS that can act on data processed by MongoDB Atlas Vector Search and deliver more accurate and relevant responses. Unlike add-on solutions that only store vector data, MongoDB Atlas Vector Search powers generative AI applications by functioning as a highly performant and scalable vector database with the added benefits of being integrated with a globally distributed operational database that can store and process all of an organization's data.

Using the integration with Amazon Bedrock, customers can privately customize FMs—from AI21 Labs, Amazon, Anthropic, Cohere, Meta, and Stability AI—with their proprietary data, convert data into vector embeddings, and process these embeddings using MongoDB Atlas Vector Search. Leveraging Agents for Amazon Bedrock for retrieval augmented generation (RAG), customers can then build applications that respond to user queries with relevant, contextualized responses—without needing to manually code. For example, a retail apparel organization can more easily develop a generative AI application to help employees automate tasks like processing inventory requests in real time or to help personalize customer returns and exchanges by suggesting similar styles of in-stock merchandise. With fully managed capabilities, this new integration will enable joint AWS and MongoDB customers to securely use generative AI with their proprietary data to its full extent throughout an organization and realize business value more quickly—with less operational overhead.

"In this next wave of widespread AI adoption, organizations want to strengthen their data strategies to develop differentiating and competitive generative AI solutions," said Vasi Philomin, Vice President of Generative AI at AWS. "The MongoDB Atlas Vector Search integration with Amazon Bedrock will help customers tightly align their data strategies to build and scale generative AI innovations. With a relationship spanning more than a decade, we look forward to continuing our momentum with MongoDB and enabling our joint customers to make the most of generative AI."

Scalestack AI is an all-in-one data enrichment, prioritization, and activation platform that allows go-to-market teams to easily map existing data to their ideal customer profile and power their sales and revenue engine. "Scalestack's mission is to help organizations unlock sales productivity, and our relationship with MongoDB has been integral to that," said Elio Narciso Co-founder and CEO at Scalestack. "We use MongoDB Atlas Vector Search to store the data we use in our RAG chatbot, and it provides long-term memory to the large language models we use. We're really excited about the integration between MongoDB Atlas Vector Search and Amazon Bedrock—this fully managed system will let our developers focus on innovating on behalf of customers. We look forward to working with both MongoDB and AWS to further the development of Scalestack's AI-powered RevOps platform."

The integration of MongoDB Atlas Vector Search with Amazon Bedrock will be available on AWS in the coming months.

About MongoDB Atlas
MongoDB Atlas is the leading multi-cloud developer data platform that accelerates and simplifies building modern applications with a highly flexible, performant, and globally distributed operational database at its core. By providing an integrated set of data and application services in a unified environment, MongoDB Atlas enables development teams to quickly build with the security, performance, and scale modern applications require. Millions of developers and tens of thousands of customers across industries—including Cathay Pacific, Cisco, GE Healthcare, Intuit, Toyota Financial Services, and Verizon—rely on MongoDB Atlas every day to innovate more quickly, efficiently, and cost-effectively for virtually every use case across the enterprise. To get started with MongoDB Atlas, visit mongodb.com/atlas.

About MongoDB
Headquartered in New York, MongoDB's mission is to empower innovators to create, transform, and disrupt industries by unleashing the power of software and data. Built by developers, for developers, MongoDB's developer data platform is a database with an integrated set of related services that allow development teams to address the growing requirements for today's wide variety of modern applications, all in a unified and consistent user experience. MongoDB has tens of thousands of customers in over 100 countries. The MongoDB database platform has been downloaded hundreds of millions of times since 2007, and there have been millions of builders trained through MongoDB University courses. To learn more, visit mongodb.com.

Forward-looking Statements
This press release includes certain "forward-looking statements" within the meaning of Section 27A of the Securities Act of 1933, as amended, or the Securities Act, and Section 21E of the Securities Exchange Act of 1934, as amended, including statements concerning enhancements of MongoDB's technology and offerings. These forward-looking statements include, but are not limited to, plans, objectives, expectations and intentions and other statements contained in this press release that are not historical facts and statements identified by words such as "anticipate," "believe," "continue," "could," "estimate," "expect," "intend," "may," "plan," "project," "will," "would" or the negative or plural of these words or similar expressions or variations. These forward-looking statements reflect our current views about our plans, intentions, expectations, strategies and prospects, which are based on the information currently available to us and on assumptions we have made. Although we believe that our plans, intentions, expectations, strategies and prospects as reflected in or suggested by those forward-looking statements are reasonable, we can give no assurance that the plans, intentions, expectations or strategies will be attained or achieved. Furthermore, actual results may differ materially from those described in the forward-looking statements and are subject to a variety of assumptions, uncertainties, risks and factors that are beyond our control including, without limitation: the impact the COVID-19 pandemic may have on our business and on our customers and our potential customers; the effects of the ongoing military conflict between Russia and Ukraine on our business and future operating results; economic downturns and/or the effects of rising interest rates, inflation and volatility in the global economy and financial markets on our business and future operating results; our potential failure to meet publicly announced guidance or other expectations about our business and future operating results; our limited operating history; our history of losses; failure of our platform to satisfy customer demands; the effects of increased competition; our investments in new products and our ability to introduce new features, services or enhancements; our ability to effectively expand our sales and marketing organization; our ability to continue to build and maintain credibility with the developer community; our ability to add new customers or increase sales to our existing customers; our ability to maintain, protect, enforce and enhance our intellectual property; the growth and expansion of the market for database products and our ability to penetrate that market; our ability to integrate acquired businesses and technologies successfully or achieve the expected benefits of such acquisitions; our ability to maintain the security of our software and adequately address privacy concerns; our ability to manage our growth effectively and successfully recruit and retain additional highly-qualified personnel; and the price volatility of our common stock. These and other risks and uncertainties are more fully described in our filings with the Securities and Exchange Commission ("SEC"), including under the caption "Risk Factors" in our Quarterly Report on Form 10-Q for the quarter ended July 31, 2023, filed with the SEC on September 1, 2023 and other filings and reports that we may file from time to time with the SEC. Except as required by law, we undertake no duty or obligation to update any forward-looking statements contained in this release as a result of new information, future events, changes in expectations or otherwise.

MongoDB Public Relations
press@mongodb.com

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SOURCE MongoDB, Inc.

FAQ

What did MongoDB, Inc. announce at AWS re:Invent 2023?

MongoDB, Inc. announced plans to integrate MongoDB Atlas Vector Search with Amazon Bedrock to enable the development of next-generation applications on AWS.

What are the benefits of the integration with Amazon Bedrock?

The integration opens up opportunities for developers to create highly engaging and customized end-user experiences.

How does MongoDB Atlas Vector Search simplify the implementation of generative AI in applications?

It uses an organization's operational data to bring generative AI and semantic search capabilities into applications, enhancing user experiences.

What are the use cases for the integration?

Developers can leverage proprietary data processed by MongoDB Atlas Vector Search to deliver up-to-date responses for a wide range of use cases.