MongoDB, Inc. is introducing a range of product innovations and AI partner ecosystem expansions to help customers build accurate, trustworthy, and reliable AI applications at scale.
According to the company, by providing industry-leading embedding models and a fully integrated, AI-ready data platform—and by assembling a world-class ecosystem of AI partners—MongoDB is giving organizations everywhere the tools to deliver reliable, performant, cost-effective AI.
MongoDB continues to invest in streamlining the AI stack and introducing more performant, more cost-effective models. Customers can integrate Voyage AI’s latest embedding and reranking models with their MongoDB database infrastructure.
MongoDB also increased its interoperability with industry-leading AI frameworks—by launching the MongoDB MCP Server to give agents access to tools and data, and by expanding its comprehensive AI partner ecosystem to give developers more choice.
These capabilities fuel substantial momentum among developers building next-generation AI applications, the company said.
“Databases are more central than ever to the technology stack in the age of AI. Modern AI applications require a database that combines advanced capabilities—like integrated vector search and best-in-class AI models—to unlock meaningful insights from all forms of data (structure, unstructured), all while streamlining the stack,” said Andrew Davidson, SVP of Products at MongoDB. “These systems also demand scalability, security, and flexibility to support production applications as they evolve and as usage grows. By consolidating the AI data stack and by building a cutting-edge AI ecosystem, we're giving developers the tools they need to build and deploy trustworthy, innovative AI solutions faster than ever before.”
Voyage AI by MongoDB recently introduced industry-leading embedding models designed to unleash new levels of AI accuracy at a lower cost:
- Context-aware embeddings for better retrieval
- New highs in model performance
- Instruction-following reranking for improved accuracy:
MongoDB also recently introduced the MongoDB Model Context Protocol (MCP) Server in public preview.
This server standardizes connecting MongoDB deployments directly to popular tools such as GitHub CoPilot in Visual Studio Code, Anthropic's Claude, Cursor, and Windsurf. This enables developers to use natural language to interact with data and manage database operations—and streamlines AI-powered application development on MongoDB, accelerating workflows, boosting productivity, and reducing time to market, the company said.
“Many organizations struggle to scale AI because the models themselves aren’t up to the task. They lack the accuracy needed to delight customers, are often complex to fine-tune and integrate, and become too expensive at scale,” said Fred Roma, SVP of engineering at MongoDB. “The quality of your embedding and reranking models is often the difference between a promising prototype and an AI application that delivers meaningful results in production. That’s why we’ve focused on building models that perform better, cost less, and are easier to use—so developers can bring their AI applications into the real world and scale adoption.”
MongoDB has also expanded its AI partner ecosystem to help customers build and deploy AI applications faster:
- Enhanced evaluation capabilities: Galileo, a leading AI reliability and observability platform, is now a member of the MongoDB partner ecosystem, which is designed to give customers flexibility and choice.
- Resilient, scalable AI applications: Temporal, a leading open-source Durable Execution platform is now also a member of the MongoDB partner ecosystem. Temporal enables developers to orchestrate reliable AI use cases built on MongoDB, including agents, RAG, and context engineering pipelines that manage and serve dynamic, structured context at runtime.
- Streamlined AI workflows: MongoDB's partnership with LangChain is redefining how developers build AI applications and agent-based systems by streamlining development and unlocking the value of customers' real-time, proprietary data.
For more information about this news, visit www.mongodb.com.