MongoDB Announces Acquisition of Voyage AI to Enable Organisations to Build Trustworthy AI Applications

MongoDB, Inc., the leading database for modern applications, announced today that it has acquired Voyage AI, a pioneer in state-of-the-art embedding and reranking models that power next-generation AI applications.

Integrating Voyage AI's technology with MongoDB will enable organisations to easily build trustworthy, AI-powered applications by offering highly accurate and relevant information retrieval deeply integrated with operational data.

AI-powered applications can address a broad range of complex use cases that traditional software cannot; however, because AI models are probabilistic, they can hallucinate––when a model generates false or misleading information.

Inaccurate or low-quality results can create serious risks––especially in cases where the accuracy of information is critical, such as a hospital performing cancer screenings, a financial firm making autonomous investment decisions, or a law firm offering legal advice.

Consequently, the risk of hallucinations has limited the use of AI applications for mission-critical use cases. These hallucinations typically occur when the AI model lacks sufficient understanding or context of data within an enterprise.

To address this challenge, companies need high-quality retrieval—a critical AI capability that ensures the most relevant information is extracted from their data with precision.

Voyage AI's advanced embedding and reranking models enable applications to extract meaning from highly specialized and domain-specific text and unstructured data—ranging from legal and financial documents to images, code, and enterprise knowledge bases. Their models are trusted by leading AI innovators like Anthropic, LangChain, Harvey, and Replit.

Notably, Voyage AI's embedding models are the highest-rated zero-shot models in the Hugging Face community. Voyage AI is a leader in AI-powered search and retrieval, backed by a team of world-class AI researchers with roots at Stanford, MIT, UC Berkeley, and Princeton.

Their expertise in cutting-edge embedding models and retrieval architectures will enhance MongoDB's AI capabilities to solve the most challenging problems with building and scaling AI applications.

"AI has the promise to transform every business, but adoption is held back by the risk of hallucinations," said Dev Ittycheria, CEO of MongoDB. "By bringing the power of advanced AI-powered search and retrieval to our highly flexible database, the combination of MongoDB and Voyage AI enables enterprises to easily build trustworthy AI-powered applications that drive meaningful business impact. With this acquisition, MongoDB is redefining what's required of the database for the AI era."

"For AI applications to reach their full potential, businesses must trust their outputs, so retrieval needs to be deeply integrated with operational data to be accurate and relevant," said Tengyu Ma, Founder of Voyage AI. "Joining MongoDB enables us to bring our cutting-edge AI retrieval technology to a broader audience and integrate it seamlessly into mission-critical applications. By combining our expertise in embeddings and reranking with MongoDB's best-in-class database, we can help organizations build AI applications that deliver more accurate and reliable results at scale, empowering them to confidently apply AI to high-stakes use cases."

What Voyage AI brings to MongoDB

Voyage AI has built a world-class AI research team with roots at Stanford, MIT, UC Berkeley, and Princeton and has rapidly become a leader in high-precision AI retrieval. Their technology is already trusted by some of the most advanced AI startups, including Anthropic, LangChain, Harvey, and Replit.

Notably, Voyage AI’s embedding models are the highest-rated zero-shot models in the Hugging Face community. Voyage AI’s models are designed to increase the quality of generated output by:

• Enhancing vector search by creating embeddings that better capture meaning across text, images, PDFs, and structured data.
• Improving retrieval accuracy through advanced reranking models that refine search results for AI-powered applications.
• Enabling domain-specific AI with fine-tuned models optimized for different industries such as financial services, healthcare, and law, and use cases such as code generation.

By integrating Voyage AI’s retrieval capabilities into MongoDB, we’re helping organizations more easily build AI applications with greater accuracy and reliability—without unnecessary complexity.

How Voyage AI will be integrated into MongoDB

We are integrating Voyage AI with MongoDB in three phases. In the first phase, Voyage AI’s text embedding, multi-modal embedding, and reranking models will remain widely available through Voyage AI’s current APIs and via the AWS and Azure Marketplaces—ensuring developers can continue to use their best-in-class embedding and reranking capabilities. We will also invest in the scalability and enterprise readiness of the platform to support the increased adoption of Voyage AI’s models.

Next, we will seamlessly embed Voyage AI’s capabilities into MongoDB Atlas, starting with an auto-embedding service for Vector Search, which will handle embedding generation automatically. Native reranking will follow, allowing developers to boost retrieval accuracy instantly. We also plan to expand domain-specific AI capabilities to better support different industries (e.g., financial services, legal, etc.) or use cases (e.g., code generation).

Finally, we will advance AI-powered retrieval with enhanced multi-modal capabilities, enabling seamless retrieval and ranking of text, images, and video. We also plan to introduce instruction-tuned models, allowing developers to refine search behavior using simple prompts instead of complex fine-tuning. This will be complemented by embedding lifecycle management in MongoDB Atlas, ensuring continuous updates and real-time optimization for AI applications.

What this means for developers and businesses

AI-powered applications need more than a database that just stores, processes, and persists data—they need a database that actively improves retrieval accuracy, scales seamlessly, and eliminates operational friction. With Voyage AI, MongoDB redefines what’s required for a database to underpin mission-critical AI-powered applications.

Developers will no longer need to manage external embedding APIs, standalone vector stores, or complex search pipelines. AI retrieval will be built into the database itself, making semantic search, vector retrieval, and ranking as seamless as traditional queries.

For businesses, this translates to faster time-to-value and greater confidence in scaling AI applications. By delivering high-quality results at scale, enterprises can seamlessly integrate AI into their most critical use cases, ensuring reliability, performance, and real-world impact.