MongoDB

The future of AI in financial services won't be built on legacy infrastructure. While "lift and shift" methods provided a quick fix in the past, true innovation requires a re-engineered approach. Learn how we're partnering with @Accenture to help financial institutions make the leap from mainframe dependency to AI-ready architecture. Watch the video 👇 mongodb.social/6017B8GIjJ

Everyone wants to “build an agent platform” until they realize they’re actually signing up to build: → Memory systems → Governance frameworks → Eval infrastructure → Orchestration layers …while the entire AI stack changes underneath them in real time. The best platform engineering decision this quarter might be deciding what not to build. MongoDB Field CTO Pete Johnson weighs in: mongodb.com/company/blog/t…

🚗 Rivian Volkswagen Tech Group manages a growing fleet of connected vehicles — each capable of generating tens of GBs of data per hour. Instead of collecting everything, they built a system on MongoDB Atlas that collects exactly the data they need, from exactly the right vehicles, without permanently increasing baseline telemetry or compromising regional data governance. See how it’s built: mongodb.social/6011B86Iol

LangGraph.js Long-Term Memory Store is now generally available. This integration brings long-term memory across sessions, across users, and across time, with Atlas as the unified backend for checkpointing and semantic recall, powered by Voyage AI embeddings. 👇 mongodb.social/6016BBfGOp

ICYMI — We announced new capabilities at #MongoDBlocal London to deliver a unified AI data platform that gives enterprises everything they need to run agents in production. 🔥 From persistent agent memory with LangGraph.js Long-Term Memory Store, to Automated Voyage Embeddings in MongoDB Vector Search, to MongoDB 8.3 performance gains, these launches are designed to help teams retrieve the right context; persist memory across sessions, channels, and frameworks; and scale AI applications in production. 🎥: mongodb.social/6011BB4G0b

🚗 Turn vehicle data into usable insights. Automotive teams generate massive volumes of vehicle data, yet finding and reusing the right data remains a challenge. Join MongoDB and @aws_partners for a joint webinar on how automotive companies and OEMs improve data discovery, access, and reuse across engineering workflows. Register now ➡️ mongodb.social/6016BBLE8I

@SunnyDhakane2 Hi Sunny, I understand that you might need some help. On the MongoDB website, please feel free to use the chat feature to share your request. The team is there to assist you and will be more than happy to help.

The Building AI Agents with MongoDB and LangGraph Skill Badge can be yours on May 28th. Here's how you earn it 👉 Join our LIVE workshop, build a real agent with MongoDB, Claude Sonnet, and LangGraph, and walk out with a new badge and the code to prove it. Claim your spot: mongodb.social/6017BBxWnv

What shipped last quarter? Episode 2 of "Between Two Leaves" highlights significant quality-of-life improvements for enterprise operators and developers, focusing on observability, disaster recovery, and the .NET ecosystem. 📺: mongodb.social/6013BBxkFB

A lot of enterprises already have AI agents in production, but few have a clear way to govern them. The challenge isn’t just the agents, but the growing number of tools behind them. When those are built in isolation, things get hard to track, harder to secure, and nearly impossible to audit. At a certain scale, this stops being manageable without shared infrastructure. Learn how a centralized tool registry is one way teams are starting to solve for that: mongodb.social/6018BBQko4

A lot shipped at MongoDB.local London today. New capabilities, new integrations, new ways to build production AI. If you weren't in the room, the livestream is on demand with everything you need to catch up. → mongodb.social/6014BBl5e4

AI-native applications don’t stay in conference rooms. Neither did we 🚕 📸 Keep an eye out across London and tag us for a chance to be featured. #MongoDBlocal

🇬🇧 🎤A full day of conversations at #MongoDBlocal London. On stage: @cj_mongodb, @UlkuRowe of @lbgplc, @LucianaLix of @Sequoia, and Alexander Holt of @Elevenlabs.

“LLMs are here to stay. The data layer is here to stay. The agent layer is here to stay. Everything else is in question.” @cj_mongodb sat down with @harrystebbings to talk about what stays constant as AI reshapes the stack, and why the data layer is at the center of it. #MongoDBlocal

We just dropped 3 🆕 AI Skill Badges 💫 Our new skill badges focus on the abilities that separate prototype AI from production AI. Earn all three, add them to your profile, and show the world you build AI that works ➡️ mongodb.social/6010BBiNoI

@VoyageAI @awscloud Stop fighting infrastructure and start building AI 💪 Learn more about everything we announced at MongoDB.local London ⬇️ mongodb.social/6010BBi0e0

@VoyageAI @awscloud We're launching three new MongoDB AI Skill Badges. 🎓 Prove your expertise building production AI on MongoDB: → Voyage AI with MongoDB → Vector Search Performance → Memory for AI Applications Earn yours today ⬇️ mongodb.social/6019BBi0eL

We shipped new capabilities at MongoDB.local London to deliver a unified AI data platform that gives enterprises everything they need to run agents in production 🔥 Here’s what’s new 👇