MongoDB

/*Think outside rows and columns.*/

[MongoDB @MongoDB]

MongoDB just announced Q2 FY2027 earnings.

📈 Total revenue of $772M, up 30% YoY.
☁️ MongoDB Atlas revenue grew ~29% YoY
🚀 EA & Other revenue grew 36% YoY
🤝 2,900 additional customers for a total of more than 70,600 total customers
🔍 @VoyageAI customers nearly doubled QoQ

We are raising full-year 2027 guidance due to strength in MongoDB Atlas. Learn more: https://t.co/2cyxvnHkYx

[MongoDB @MongoDB]

Big stage, big names. Here's who is taking the stage for #MongoDBlocal NYC 👇

→ @cj_mongodb , President and CEO
→ Erica Volini, Chief Customer Officer
→ Ashish Kumar, Senior Vice President and Technical Fellow
→ @bencefalo, Chief Product Officer, Core Products

They'll be joined by customers like @okta, @ACI_Worldwide, @Wayfair, @coinbase, and more for a full day of talks, demos and technical sessions, all focused on real AI use cases.

🗽✨ Full agenda: https://t.co/twRJlvlqVf

[MongoDB @MongoDB]

Retrieving 20 chunks "to be safe" burns ~10K tokens a call on mostly noise, and it often makes answers worse, not better.

We cut that by 80% with a simple pipeline on MongoDB Atlas and @VoyageAI: quantized embeddings to shrink storage and reranking to send only the top few chunks to the LLM.

Get the full breakdown: https://t.co/GAJR1ONhxW

[MongoDB @MongoDB]

AI starts with the data.

And if your data foundation is stuck in the past, your AI ambitions could be too.

New IDC research reveals that APAC organizations leading the way in modernization are generating nearly 3x the regional average in digital revenue.

Explore what it takes to modernize legacy infrastructure and build a foundation for AI.

Read the research: https://t.co/gNMtsEywb5

[MongoDB @MongoDB]

MongoDB Atlas is turning 10! Gabriel Woo, Regional Vice President Greater China Region at MongoDB, shares his "Atlas moment:" watching enterprises like Cathay Pacific move mission-critical workloads to a fully managed, run-anywhere platform.

Learn more about what's next for Atlas: https://t.co/cjFBgp2Pbx

[MongoDB @MongoDB]

We took to the floor at MongoDB.local Build Fest in San Francisco to ask people one question: What's one skill developers should practice more?

Their answers... may or may not surprise you. 👀

What should we ask next? Let us know in the comments 👇

[MongoDB @MongoDB]

@ESBG7 Hi Elías, please request access to our Trust Portal - https://t.co/POelsEhwvv, you should be able to download the SOC 2 report once your account is approved. If you face any further issues please reach out to our support team on our website.

[MongoDB @MongoDB]

💭 What are you building with MongoDB right now?

Tell us in r/MongoDB_Official, our new home for the builder community to connect, ask questions, and share wins. ���� https://t.co/BD2q3aAUGz

[MongoDB @MongoDB]

@razaaitech Make sure to join our community! 💚

[MongoDB @MongoDB]

@ianlivingstone @MelGoesTech @KeycardAI We sure did! 😎

[MongoDB @MongoDB]

Your archive is an untapped opportunity.

@brahma_ai helps media and entertainment companies orchestrate content end to end, from creation and management to distribution across social, broadcast, and theaters.

However, unlocking the value of massive content libraries requires flexibility.

That’s why Brahma AI moved from a traditional RDBMS to MongoDB, creating a foundation for complex media metadata and AI-enriched content.

The result? AI agents can help enterprises discover content that was once “sleeping” in their archives, and turn it into something they can actually use and monetize.

Read how Brahma AI is modernizing media content workflows here: https://t.co/f7yIuQJOW1

[MongoDB @MongoDB]

“Every system an agent reaches into is another credential and another place for that view to drift.” - Jess Yan, Product Lead for @claudeai Managed Agents at @AnthropicAI

Fraud review needs semantic precedent, exact-match lookups, and network traversal on the same case. This is usually handled by stitching together three or four separate systems, each with its own credential for the agent to manage.

In this new tutorial from Sai Teja Boddapati, Staff Solutions Architect at MongoDB, you’ll learn how to build a human-in-the-loop fraud-review agent on Anthropic’s Claude Managed Agents, using one MongoDB Atlas cluster as its retrieval engine, graph store, and system of record.

This stack ensures that your agent is always working from one source of truth, so there's nothing separate to fall out of sync and risk feeding it stale context.

Everything you need to get started: https://t.co/8aduZ0w9FB

[MongoDB @MongoDB]

Regulatory and standards content can be difficult to search when requirements are revised, referenced differently, or spread across multiple sources.

For automotive engineering and compliance teams, MongoDB Atlas combines lexical and vector search to help users find relevant CMVR and AIS content, while preserving the context needed to verify what they’ve found.

Key takeaways:
✅ Hybrid search supports both exact identifiers, like rule numbers, and natural-language queries.
✅ Provenance stays intact, including rule/section, revision, effective date, and source locator.
✅ The approach scales across standards, including CMVR/AIS, UNECE, FMVSS, and GB.
✅ Search helps users find and verify source material, it does not provide legal, regulatory, or compliance advice.

Explore the solution:
https://t.co/vithceQWTB

[MongoDB @MongoDB]

@codesbyshivam MongoDB socks: officially part of the stack. 😂🧦

[MongoDB @MongoDB]

The shopping agent in your favorite app understands what you want, checks what's actually in stock, and finishes checkout. 🛍️

Built with @crewAIInc + MongoDB Atlas Vector Search.

Full breakdown, code included 👉
https://t.co/JYeogPdDM1

[MongoDB @MongoDB]

“What if we changed this?” For network operators, that question can have serious consequences.

AI agents could change the equation, letting teams explore scenarios, understand dependencies, and test their next move before putting it into production.

From intent to what-if, the future of network operations is becoming more predictive.

Read the blog: https://t.co/neRnS173Bs

[MongoDB @MongoDB]

MongoDB Atlas is now a connected data source in @OpenAI's Data agent for @ChatGPT Work, powered by the MongoDB Atlas Managed MCP Server.

Analysts and business teams can now point the Data agent at their live Atlas clusters and ask what changed, why it changed, and what to look at next, then turn the answer into a report or real-time dashboard without leaving the chat.

Get started: https://t.co/BmpuEvh1s4

[ChatGPT @ChatGPT]

Now everyone can put data to work.

We’re introducing a new Data agent in ChatGPT Work so you can turn your company’s data into answers, interactive dashboards, and action—just by asking.

Just add the Data Plugin in ChatGPT Work, connect to the data sources and context you already use, and start the conversation. https://t.co/EG1nQFZfEU

[MongoDB @MongoDB]

@samirande_ We’ll take it. 😌💚

[MongoDB @MongoDB]

One click. That's all it takes to now open MongoDB Atlas directly from @vercel.

If you're using the MongoDB Atlas Vercel Native Integration, you can now jump directly from Vercel to your Atlas organization or project, using the credentials you already have.

Learn more: https://t.co/LZ1uCONfqh

[MongoDB @MongoDB]

@ArjungondCodes No Googling needed. 😉

[MongoDB @MongoDB]

@WizzHQ Onchain, social, market data… sounds like MongoDB territory. 😉