MongoDB NASDAQ: MDB CEO CJ Desai outlined the company’s focus on enterprise modernization, AI-native customers and product enhancements during Citi’s TMT Conference, following what he described as a strong fiscal second-quarter report.
Desai said MongoDB reported total revenue growth above 30% in the quarter, marking what he called the company’s first time reaching that growth level “in a long time.” He also said the company is pursuing durable growth alongside increasing profitability, citing operating-margin and cash-flow results released the prior week.
After roughly a year as CEO, Desai said he sees three primary areas of opportunity: broader enterprise adoption, demand from AI-native companies and early engagement with frontier AI labs.
Enterprise modernization and global demand
Desai said MongoDB is increasingly becoming a standard platform for modern database deployments at large enterprises, particularly in financial services and insurance, where companies are managing unstructured data and moving toward multicloud environments.
He also cited early public-sector demand and international opportunities. In Europe, he said sovereign-cloud requirements have supported demand for MongoDB’s ability to be self-managed and deployed across environments. In India, Desai pointed to digital-native companies, including Zomato, that are building on MongoDB.
The company is also putting greater emphasis on executive-level relationships with chief information officers, chief technology officers, chief data officers and enterprise architects. Desai said some large customers spending seven- or eight-figure annual recurring revenue amounts had not fully recognized the extent of their MongoDB usage across mission-critical workloads.
Those conversations are also opening opportunities around AI readiness and modernization, according to Desai. He said MongoDB is discussing ways to help enterprises migrate certain workloads from aging relational databases, with the goal of reducing migration projects from years to months or from months to weeks.
AI-native customers and frontier labs
Desai said many AI-native companies initially used PostgreSQL or hyperscaler-provided database services before encountering scaling constraints and moving to MongoDB. He said companies such as Mercor, ElevenLabs and Harvey have become examples of businesses using MongoDB as a foundational operational data layer.
He identified three product attributes that he believes are driving adoption for AI workloads:
- MongoDB’s JSON-native document model, which Desai said aligns with the structure and speed of AI development;
- Its ability to scale out for large workloads; and
- Its ability to run across cloud environments, including configurations spanning multiple hyperscalers.
For AI labs, use cases vary, Desai said. One example involves using MongoDB as a conversational memory layer for agent interactions. At ElevenLabs, he said MongoDB supports real-time agent workloads involving speech-to-text, text-to-speech and significant volumes of unstructured data.
Desai said enterprise adoption of customer-facing AI agents remains earlier than adoption of internal-facing AI applications. He expects technology companies, including cybersecurity providers, to be among the earlier enterprise adopters of external-facing agent deployments. Retail and financial services could follow, he said, while manufacturing and consumer packaged goods may take longer.
Atlas, developer tools and customer additions
Addressing investor attention on Atlas growth, Desai said MongoDB’s core business differs from data warehouse and observability peers because its workloads are generally customer-facing rather than employee-facing. He said Atlas consumption could increase as enterprises deploy customer-facing agents at scale.
The company recently introduced automatic embeddings capabilities using Voyage AI and launched generally available fully managed Model Context Protocol functionality for Claude Code, Codex and Grok Build on Aug. 13, according to Desai. He said MongoDB had seen higher Atlas traffic in the roughly three-and-a-half weeks after the MCP launch and expects to provide additional information at its Investor Day on Sept. 29.
Desai said the fully managed MCP functionality could make it easier for developers to build and provision Atlas clusters through coding-agent tools. He also said Voyage customer additions have been strong, with many referrals coming from Claude Code and Codex. MongoDB sees those Voyage users as a potential top-of-funnel opportunity for Atlas.
The company added approximately 2,900 customers, its highest quarterly level, according to the conference discussion. Desai said about 99% of new customer additions are on Atlas. He added that MongoDB is focused on attracting workloads that can scale meaningfully rather than prioritizing lower-scale internal applications.
Go-to-market priorities and migrations
Head of Investor Relations Jess Lubert said MongoDB continues to see particular strength among its largest North American customers. She identified U.S. federal and Asia-Pacific as areas for improvement. The company is investing in FedRAMP High and sees Japan as a significant database market, while making go-to-market changes across Asia.
Desai said MongoDB’s net revenue retention rate was 122%, with both self-managed and Atlas offerings contributing healthy retention results.
On database migrations, Desai said MongoDB is shifting from a services-heavy approach to a more product-driven strategy. The company is working with large design partners to improve tools that can migrate workloads from relational databases to Atlas more quickly. He said MongoDB expects to invest more heavily behind that effort in the next fiscal year once the product is ready.
Looking ahead, Desai said MongoDB’s priorities are to remain the best database across self-managed and Atlas deployments, make MongoDB more appealing to coding agents and establish the platform as a default real-time operational data layer for AI workloads.
About MongoDB (NASDAQ:MDB)
MongoDB, Inc develops database software and data platform services for organizations building, deploying and operating modern applications. Its flagship technology is a document-oriented database that stores data in flexible, JSON-like documents, helping developers manage varied data structures and support applications that require scalability and rapid development.
The company offers MongoDB Atlas, a fully managed cloud database service available across major cloud providers, as well as MongoDB Enterprise Advanced for organizations that operate databases in private, hybrid or multicloud environments.
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