MongoDB Makes Enterprise AI Production Ready

Unified Data Platform Delivers Native Embeddings Generation, Persistent Agent Memory, and
Real-Time Operational Data

LONDON, May 7, 2026 /PRNewswire/ -- MongoDB, Inc. (NASDAQ: MDB) today announced new capabilities at MongoDB local London 2026, furthering its vision and strategy of delivering a unified AI data platform that gives enterprises everything they need to run agents in production—a real-time database, full text and vector search, memory, embeddings, and reranker models—all in one platform. Until now, enterprises have had to stitch together disparate systems and to hope they would work together at scale. MongoDB has solved that.

"The hardest part of running agents in production isn't the model. It's the data layer underneath it," said CJ Desai, President and Chief Executive Officer of MongoDB. "To trust an agent at scale, it has to retrieve the right context, hold memory across sessions, and operate at machine speed, wherever the enterprise needs it. That's why AI-native companies like ElevenLabs build voice agents on MongoDB, and why institutions like Lloyds Banking Group trust it for mission-critical workloads."

Retrieval accuracy

With Automated Voyage AI Embeddings in MongoDB Vector Search, now in public preview, embeddings are now generated automatically as data is written or updated to give agents accurate, real-time context.

Agents are only as good as what they remember and what they can retrieve. Embedding models convert information into vectors—an array of numbers that represent meaning mathematically—so an agent can find the right information. MongoDB's Voyage AI embedding models rank #1 on the Retrieval Embedding Benchmark (RTEB). This means agents built on MongoDB can accurately find the right information.

Automated Voyage AI Embeddings removes the manual infrastructure work that has historically stood between enterprises and accurate AI search. Enterprises that previously spent weeks building search infrastructure can now ship semantic search in minutes.

High accuracy requires strong memory. Agents without memory can't learn, improve, or be trusted. The LangGraph.js Long-Term Memory Store, now generally available, gives JavaScript and TypeScript developers persistent, cross-conversation agent memory that Python developers have had—powered by MongoDB Atlas, as a single backend, with no additional database required.

"When AI tools and agents produce a wrong answer, the instinct is to blame the model," said Pablo Stern, Chief Product Officer, AI and Emerging Products at MongoDB. "But the data platform is what enables the agent with the right context and memory to act correctly. With MongoDB, we've made this easy. Developers no longer have to build and maintain data infrastructure, wire up embeddings, or manage syncing between systems. They can focus on business outcomes rather than the plumbing."

Performance under pressure

MongoDB 8.3, available today, delivers up to 45% more reads, 35% more writes, 15% more ACID transactions, and 30% more complex operations over MongoDB 8.0—without changing a line of application code.

When enterprises like Adobe need to scale to serve Fortune 500 marketing teams on one of the world's most widely used platforms, the requirements are clear: sub-100ms retrieval, sub-second context updates, and zero downtime. MongoDB Atlas is built for AI speed.

"The requirements of enterprises running AI at scale are what we build for. MongoDB 8.3 makes agent workloads faster and cheaper to run on infrastructure customers already have. We've also moved common data transformations into the database itself, so teams no longer have to maintain external pipelines just to feed their agents. Production AI doesn't wait, and neither do we," said Ben Cefalo, Chief Product Officer, Core Products at MongoDB.

Run anywhere

For banks, healthcare organizations, and government agencies, deployment choice isn't optional. It's often a data residency requirement set before architecture enters the conversation.

MongoDB runs across Amazon Web Services (AWS), Google Cloud, Microsoft Azure, on-premises, and in hybrid environments. Customers get one database, one API, and one set of skills that work consistently wherever they deploy.

Cross-region connectivity for AWS PrivateLink, now generally available, ensures that database traffic between MongoDB Atlas clusters in different AWS regions stays on the AWS private network, with no exposure to the public internet. That helps security teams approve cross-region architectures faster, with fewer exceptions, and without forcing a tradeoff between compliance and global reach.

With these announcements, MongoDB continues to deliver what enterprises need to run AI agents in production—all in one platform.

What's new at MongoDB.local London 2026:

• Automated Voyage AI Embeddings in MongoDB Vector Search for Atlas — Public Preview
• MongoDB 8.3 — Generally Available
• LangGraph.js Long-Term Memory Store Integration — Generally Available
• Cross-Region Connectivity Support for AWS PrivateLink — Generally Available
• Feast Feature Store Integration with MongoDB — Generally Available
• New Query Expressions for Data Transformation — Generally Available
• MongoDB AI Skill Badges — Generally Available

About MongoDB
Headquartered in New York, MongoDB's mission is to empower innovators to create, transform, and disrupt industries with software. MongoDB's unified database platform was built to power the next generation of applications, and MongoDB is the most widely available, globally distributed database on the market. With integrated capabilities for operational data, search, real-time analytics, and AI-powered data retrieval, MongoDB helps organizations everywhere move faster, innovate more efficiently, and simplify complex architectures. Millions of developers and more than 65,200+ customers across industries – including ~75% of the Fortune 100 – rely on MongoDB for their most important applications. 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 new capabilities announced at MongoDB .local London 2026. 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: our customers renewing their subscriptions with us and expanding their usage of software and related services; global political changes; the effects of the ongoing military conflicts between Russia and Ukraine and Israel and Hamas and recent events in Venezuela 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; reputational harm or other adverse consequences resulting from use of AI and ML in our product offerings and internal operations if they don't produce the desired benefits; our limited operating history; our history of losses; our potential failure to repurchase shares of our common stock at favorable prices, if at all; 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, including AI and ML; social, ethical and security issues relating to the use of new and evolving technologies, such as artificial intelligence, in our offerings or partnerships; 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; our ability to continue to increase revenue from our Atlas platform; the effects of social, ethical and regulatory issues relating to the use of new and evolving technologies, such as AI and ML, in our offerings or partnerships; the growth and expansion of the market for database products and our ability to penetrate that market; 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; our ability to integrate acquisitions and work with our strategic partners effectively; 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 Annual Report on Form 10-K for the fiscal year ended January 31, 2026, filed with the SEC on March 11, 2026. Additional information will be made available in 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.

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SOURCE MongoDB, Inc.