MongoDB

Today at MongoDB.local Bengaluru, we announced new capabilities designed to help teams move AI into production with increased accuracy and deployment flexibility. Here’s what shipped: ✅ voyage-context-4 ✅ Public Preview: Native Reranking ✅ Search and Vector Search in MongoDB Enterprise Advanced and Community Edition ✅ Hybrid Search ✅ Apache Iceberg Support in Atlas Stream Processing ✅ Gen2 Atlas M30+ Dedicated Clusters on AWS See these and more: mongodb.social/6012BDakGp #MongoDBlocal

Build smarter with Codex + MongoDB 🚀 Stop context-switching and start interacting with your data directly. With the official MongoDB Codex Plugin, your agents connect to your MongoDB database via the MCP Server and use pre-built skills for data modeling, query optimization, MongoDB Search, Vector Search, and more. Check out the video and start working smarter today: mongodb.social/6018BEdVnq

Fresh off MongoDB.local Bengaluru, the latest episode of Between Two Leaves takes you through 7 new launches: -Hybrid Search GA -Search & Vector Search GA everywhere -Gen2 Atlas Clusters -Iceberg support -Native Reranking preview -voyage-context-4 🎥 Watch now! mongodb.social/6014BEciSG

NEW: Inside AI's Biggest Downstream Winner.. the Surge in AI Database Demand "Data is the unsung hero, & data is back." @MongoDB CEO CJ Desai (@cj_mongodb) The unexpected result? Hyperscalers are turning away even top-50 accounts. "Sorry, we don't have a capacity." "And they are one of the top 50 customers for that hyperscaler." ElevenLabs alone runs "north of 50 million agents, depending on when you look at it, all running on MongoDB.. that gives us a lot of confidence that we have the right architecture for agentic workloads." NASDAQ: $MDB We cover: › The 3 classes of AI customers MongoDB serves › Why hyperscalers are telling top-50 accounts "no capacity" › On-prem, sovereign AI, and the data-center comeback › ElevenLabs running 50M+ agents on MongoDB › MongoDB (OLTP) vs Snowflake & Databricks (OLAP) › Why there is no standardization in enterprise AI models › Auto-scaling & the fall of expensive DBAs 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) CJ Desai, CEO at MongoDB (01:12) Top CEOs at the Raise AI Summit (03:24) The 3 types of companies powering the AI boom (07:25) Why on-prem is making a shocking comeback (09:01) Hyperscalers are quietly running out of capacity (11:06) What actually separates MongoDB from Snowflake x Databricks (13:18) Why Frontier Labs treat MongoDB as their memory layer (16:22) From Oracle intern to first-time CEO (19:19) Becoming CEO during the AI chaos (23:53) The World Cup crisis that tested MongoDB's scale (28:19) The real complexity behind simple AI agents (31:22) Open source vs. closed models: what customers actually pick (34:36) CJ's honest take on data centers in space (36:50) The mentors who shaped a first-time CEO (40:32) MongoDB's next big bets (41:36) Data is back?

Most retrieval pipelines send too much to the LLM. Not because builders want them to, but because filtering low-relevance results used to mean adding a separate vendor, a new API, and more pipeline complexity. Most teams decide it isn't worth it. Native Reranking in MongoDB Atlas changes that. ⭐️ Now in public preview: a $rerank stage that runs inside the aggregation pipeline, powered by @VoyageAI by MongoDB, with no external round-trips. Up to 30% better retrieval quality on the MAIR benchmark, nothing added to your stack. See how native reranking fits your pipeline → mongodb.social/6010BEj6op

San Francisco, it’s time to build. Bring your next big idea to Build Fest. A full day of hands-on workshops, bootcamps, live demos, and 1:1 office hours — building agents and AI apps directly on MongoDB, with the people who build the platform. See you August 13 👉 mongodb.social/6019BEdifU

🎉 We're celebrating 10 years of MongoDB Atlas! Hear from Benjamin Flast, Senior Director, Product Management at MongoDB, on how Atlas grew from a managed cloud database to a unified data platform used by nearly 70,000 organizations around the world. See what's next for Atlas: mongodb.social/6014BEkfn2

Did you hear? Search and Vector Search for MongoDB Enterprise Advanced (EA) is now GA. 🛡️ Deploy fully integrated advanced search and semantic retrieval for mission-critical workloads on-premises and in private or hybrid clouds. Experience it today: mongodb.social/6017BEbhRR

When teams call their AI agent "unreliable," they usually mean one of two things: it returned a wrong answer (a memory or model problem), or it can't resume work it already finished (a state problem). Most teams govern state and memory under one lifecycle and one store, and that collapse is behind a lot of the "unreliability" they're seeing. Research on real agent failures keeps landing on the same conclusion: replaying an agent's steps after a crash isn't safe, because the agent can "redo" a task slightly differently the second time — even double-charging a customer in one case. The fix isn't a better tool, it's replaying the recorded decision instead of asking the agent to decide again. Learn the five state architectures teams ship in production, with the trade-offs of each 👉 mongodb.social/6010BEb37j

Chatbots are old news. Agentic AI is the real shift — autonomous systems that execute multi-step workflows, not just chat. We break down the 3 waves of AI evolution: 🧠 LLMs — built-in knowledge 🔍 RAG — context-rich retrieval 🤖 Agentic AI — fully autonomous, multi-step execution Plus, a real telecom use case showing how MongoDB powers it all as the stateful backbone behind high-volume, unstructured data and vector search. Watch the full video: mongodb.social/6018BEkA26

🇮🇳 Bengaluru showed up. Here's what it looked like.. Workshops, deep dives, live demos, and a community of builders who are already shipping AI in production. 🎥 Watch the full general session here → mongodb.social/6015BEXnyz 🌉 San Francisco, see you August 13th. mongodb.social/6017BEXny3

Spotted at MongoDB.local Bengaluru: The hottest tech print drop of the year. 🔥📖 Missed out on grabbing a physical copy? No problem, the digital version is ready for you here: mongodb.social/6015BEndmz

A memorable day of learning, collaboration, and community. 🎓💚 At our Gurgaon office, Industry Immersion Day brought together students, educators, and MongoDB teams for conversations that bridged classroom concepts with real-world data and careers in technology. Proud to be driving MongoDB for Academia as we continue working toward upskilling 2 million learners across India.

BREAKING: CEO of @MongoDB “CJ” Desai (@cj_mongodb) says "Data is so back" "Data is the unsung hero, & data is back. You cannot create an AI application without a great data layer. Your AI application is as good as your data." Facts.

Please welcome this year’s new cohort of MongoDB Champions! 💚 Representing countries around the world and a wide range of roles, this year’s cohort is made up of community leaders who share their knowledge, support fellow builders, and help others discover what’s possible with MongoDB. As MongoDB continues to grow, so does the community. Read here now: mongodb.social/6016BEEuqK

“You have to be flexible to move fast.” — @cj_mongodb, President & CEO of MongoDB, in conversation with @LauraModiano (OpenAI) at #RAISESummit, on why rigid infrastructure is the enemy of agentic applications. @OpenAI's own pace makes the point: models that used to take 15 months to ship now ship in six weeks. Your data layer has to keep up.

@VoyageAI Gen2 Atlas M30+ Dedicated Clusters on @awscloud are now generally available. ⚡ Next-generation infrastructure delivering a massive performance and independent IOPS scaling leap. mongodb.com/company/blog/p…

@VoyageAI voyage-context-4 is now generally available. 🧠 Drop-in contextualized embeddings with document-level context and built-in auto-chunking. @VoyageAI blog.voyageai.com/2026/06/29/voy…

Today at MongoDB.local Bengaluru, we announced new capabilities designed to help teams move AI into production with increased accuracy and deployment flexibility. Here’s what shipped: ✅ voyage-context-4 ✅ Public Preview: Native Reranking ✅ Search and Vector Search in MongoDB Enterprise Advanced and Community Edition ✅ Hybrid Search ✅ Apache Iceberg Support in Atlas Stream Processing ✅ Gen2 Atlas M30+ Dedicated Clusters on AWS See these and more: mongodb.social/6012BDakGp #MongoDBlocal

🚨 ICYMI: MongoDB is hosting a Reddit AMA TOMORROW 7/8 at 12pm ET @ r/ContextEngineering! 🚨 Max Marcon, Mikiko Bazeley, and Yang Li will be answering all your burning questions about multi-agent systems, agent memory, and the context mistakes that can kill agent systems in production. Start thinking of questions 👉 mongodb.social/6011BDNgRW

India’s AI ambition will be powered by its builders. 💻 We’re excited to expand MongoDB for Academia, with a commitment to upskill 2 million builders in India by 2030. Because the future of AI won’t just be defined by technology. It will be defined by the people empowered to build with it. Read more: mongodb.social/6014BEDbKG

June was action packed for our MongoDB community! 💚 Congratulations to our MongoDB Champion of the Month, Xiaolei Dai, our MUG Leaders of the month, Mohamed Amr and Sandeep Chavan, our Creator of the Month Farhan Hasin Chowdhury, and startup of the month, @tryhuntr! Find all the happenings in the MongoDB Community Hub!: mongodb.social/6017BEBOy5