MongoDB, Inc. has announced a major expansion of its AI capabilities at MongoDB.local San Francisco, integrating Voyage AI's advanced embedding and reranking models directly into its core database platform. This creates a unified data intelligence layer for production AI applications, allowing developers to build and scale sophisticated systems with reduced hallucination risks while eliminating the need to move or duplicate data.
Quick Intel
These enhancements address key production challenges in AI, where fragmented data stacks create complexity, latency, and reliability issues. By unifying operational data, semantic search, and retrieval in one platform, MongoDB simplifies architectures and enables faster, more dependable AI deployment for mission-critical workloads.
The Voyage 4 series delivers state-of-the-art performance: voyage-4 as a balanced general-purpose model, voyage-4-large for maximum retrieval accuracy, voyage-4-lite for optimized speed and cost, and open-weights voyage-4-nano for local or on-device use. voyage-multimodal-3.5 advances unified processing of text, images, and now video, improving semantic capture from diverse sources like PDFs, slides, and graphics without extensive parsing.
Automated Embedding, now in public preview for MongoDB Community (with Atlas support coming soon), automatically creates high-fidelity embeddings using Voyage AI models during data operations. This keeps vectors current with live data changes, removes external pipeline dependencies, and supports popular drivers and frameworks such as LangChain and LangGraph.
"The biggest challenge customers face with AI isn't experimentation, it's operating reliably at scale," said Fred Roma, Senior Vice President of Product and Engineering at MongoDB. "Developers want fewer moving parts and clearer paths from prototype to production. With today's launches, MongoDB is raising the bar, helping teams reduce complexity and focus on building AI applications that perform in real-world, mission-critical environments."
"We were looking for extremely accurate embedding models, and Voyage AI provided accuracy at scale," says Sudheesh Nair, Cofounder and CEO of TinyFish. "The Python APIs that Voyage comes out of the box with are also extremely lightweight and very fast."
"Today, companies need to move extremely fast, and at very lean startups, you need to only focus on what you are building," said Rotem Weiss, CEO of Tavily. "MongoDB allows us to focus on what matters most, our customers and our business."
Additional features include native Atlas APIs for embedding and reranking with enterprise security and performance, an intelligent AI assistant for Compass and Atlas Data Explorer to assist with natural-language data tasks, and a new AI skills certification program to build team expertise.
Trusted by over 60,000 customers, including more than 75% of the Fortune 100, MongoDB strengthens its role as the leading AI-ready data platform, empowering developers to transition AI innovations from prototypes to reliable, scalable production systems.
About MongoDB
Headquartered in New York, MongoDB's mission is to empower innovators to create, transform, and disrupt industries with software. MongoDB's unified data platform was built to power the next generation of applications, and MongoDB is the most widely available, globally distributed database on the market. With integrated capabilities for operational data, search, real-time analytics, and AI-powered data retrieval, MongoDB helps organizations everywhere move faster, innovate more efficiently, and simplify complex architectures. Millions of developers and more than 60,000 customers across industries—including over 75% of the Fortune 100—rely on MongoDB for their most important applications.
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