MongoDB Acquires Voyage AI for $220 Million to Enhance AI Application Capabilities

Voyage AI Acquisition Adds Advanced Tech, Talent to MongoDB's AI Capabilities: Analyst - MongoDB (NASDAQ:MDB)

Goldman Sachs analyst Kash Rangan maintained a Buy rating and price forecast for MongoDB, Inc. MDB following the company's acquisition of Voyage AI on Monday. MongoDB told Bloomberg that the purchase consideration was $220 million under a cash-and-stock deal. The analyst says that they believe that the buyout of Voyage AI will strengthen MongoDB's AI product roadmap and position within the modern data stack. This is mainly due to Voyage's advanced text embedding and reranking models, which enhance organizations' ability to create RAG-enabled AI applications with better contextual relevance, cost efficiency, and reduced latency, adds the analyst. Rangan notes that Voyage's flagship general-purpose and multilingual embedding model, voyage-3-large (released January 7, 2025), surpasses OpenAI-v3-large and Cohere-v3-English by an average of 9.74% and 20.71%, respectively, in retrieval quality, according to Voyage AI. Additionally, Voyage AI's voyage-3-large sets a new accuracy-cost benchmark, using advanced techniques like quantization-aware training and Matryoshka learning to reduce storage costs and processing times with minimal impact on retrieval quality, says the analyst. Overall, the analyst views this as a valuable acquisition of both technology and talent for MongoDB, with Voyage's models (set for integration later this year) offering top-tier embedding models that provide performance and cost benefits, potentially fast-tracking AI production workloads on MongoDB's platform. This aligns with the analyst's expectation of 20%+ Atlas revenue growth in the near-to-medium term. With Atlas now accounting for approximately 70% of revenue and consistently growing at over 20% since its launch, the analyst sees strong potential for sustained growth in the medium term and the ability to reach $6 billion-$8 billion+ in revenue in the long run. Investors can gain exposure to the stock via TrueShares Technology, AI & Deep Learning ETF LRNZ and Sterling Capital Focus Equity ETF LCG. Price Action: MDB shares closed down by 2.77% at $259.71 on Tuesday. Read Next: PayPal Eyes Double-Digit EPS Growth By 2027, Teams Up With Verifone, J.P. Morgan & More Photo via Shutterstock MDBMongoDB Inc$259.71-2.77%OverviewLCGSterling Capital Focus Equity ETF$31.00-1.17%LRNZTrueShares Technology, AI & Deep Learning ETF$39.98-2.26%Market News and Data brought to you by Benzinga APIs

MongoDB acquires Voyage AI to boost AI-powered application capabilities By Investing.com

Investing.com -- MongoDB , Inc. (NASDAQ:MDB), a leading modern application database provider, has announced the acquisition of Voyage AI, a company specializing in advanced embedding and reranking models for AI applications. This integration will allow organizations to build reliable, AI-powered applications by providing precise and pertinent information retrieval deeply integrated with operational data. Dev Ittycheria, CEO of MongoDB, stated that the integration of advanced AI-powered search and retrieval capabilities into their flexible database system will facilitate enterprises in building reliable AI applications that can create significant business impact. He further stated that the acquisition of Voyage AI repositions MongoDB's database requirements to meet the demands of the AI era. Tengyu Ma, founder of Voyage AI, emphasized that for AI applications to be fully effective, businesses must trust their outputs. He added that integrating retrieval with operational data ensures accuracy and relevance. The partnership with MongoDB allows Voyage AI to extend its innovative AI retrieval technology to a wider audience and integrate it efficiently into mission-critical applications. The collaboration of Voyage AI's expertise in embeddings and reranking with MongoDB's top-notch database will aid organizations in constructing AI applications that deliver more accurate and reliable results at scale. This will empower them to confidently apply AI to high-stakes use cases. Voyage AI's embedding and reranking models will continue to be accessible through voyage.ai, AWS Marketplace, and Azure Marketplace. More MongoDB integrations are expected to be launched later this year.

MongoDB Expands AI Capabilities With Voyage AI Deal, Targets Faster Insights From Unstructured Data - MongoDB (NASDAQ:MDB)

On Monday, MongoDB, Inc MDB announced it had acquired Voyage AI, which powered advanced AI applications. Integrating Voyage AI's technology with MongoDB will enable organizations to build credible, AI-powered applications quickly. MongoDB told Bloomberg that the purchase consideration was $220 million under a cash-and-stock deal. 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. Also Read: Lam Research Unveils AI Chipmaking Tools, Projects Big Returns AI innovators like Anthropic, LangChain, Harvey and Replit leveraged Voyage AI's models. MongoDB held $2.3 billion in cash and equivalents as of October 31, 2024. Reportedly, Snowflake Inc SNOW and Databricks Inc invested in Voyage AI in 2024. Gartner expects global semiconductor revenue to reach $626 billion in 2024, up 18.1%. Graphics processing units (GPUs) and AI processors for data center applications were the key drivers for the chip sector in 2024. Gartner expects the revenue to reach $705 billion in 2025, backed by demand for AI and generative AI (GenAI) workloads. MongoDB stock plunged 42% in the last 12 months. In December, the company announced that COO and CFO Michael Gordon would depart on January 31, 2025. Serge Tanjga will take over as interim CFO beginning February 1, pending a replacement. Price Action: MDB stock is down 3.72% at $263.05 at last check Monday. Also Read: User Engagement And High-Margin Businesses Fuel Bilibili Q4 Growth, CEO Highlights AI Potential Photo: Shutterstock MDBMongoDB Inc$264.00-3.39%OverviewSNOWSnowflake Inc$170.64-4.08%Market News and Data brought to you by Benzinga APIs

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

MongoDB to integrate Voyage AI's industry-leading embedding and reranking models, delivering highly accurate and relevant information retrieval to power sophisticated AI use cases MongoDB, Inc. (NASDAQ: MDB), the leading database for modern applications, today announced 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 organizations 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." Voyage AI's embedding and reranking models will remain available through voyage.ai, AWS Marketplace, and Azure Marketplace, with further MongoDB integrations launching later this year. For a deeper look at the technology behind Voyage AI and what this means for AI-powered applications, see the MongoDB blog here. About MongoDB Headquartered in New York, MongoDB's mission is to empower innovators to create, transform, and disrupt industries with software and data. MongoDB's unified, intelligent 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 retrieval, MongoDB helps organizations everywhere move faster, innovate more efficiently, and simplify complex architectures. Millions of developers and more than 50,000 customers across almost every industry -- including 70% of the Fortune 100 -- rely on MongoDB for their most important applications.

MongoDB Looks To Improve AI Application Accuracy With Acquisition

The data and AI platform company said today that it has acquired Voyage AI, a startup developing data search and retrieval technology that helps organizations build more trustworthy AI applications and improve the quality of AI outcomes. Data development platform company MongoDB has acquired Voyage AI, a developer of "embedding and rerank" AI models that improve the accuracy and efficiency of RAG (retrieval-augmented generation) data search and retrieval operations. MongoDB plans to add the Voyage AI technology to its platform to help businesses and organizations build more trustworthy AI applications that deliver more accurate results with fewer hallucinations. "AI has the promise to transform every business, but adoption is held back by the risk of hallucinations," said Dev Ittycheria, MongoDB CEO, in a statement announcing the acquisition. [Related: Changing Of The Channel Guard At 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," Ittycheria said. MongoDB's developer data platform, based on its Atlas cloud database, has become a popular system for building AI-powered applications. Last May the company launched its MongoDB AI Applications Program (MAAP), which provides a complete technology stack, services and other resources to help partners and customers develop and deploy at scale applications with advanced generative AI capabilities. One hurdle to broader generative AI use has been the technology's tendency to hallucinate or make up data and deliver inaccurate results. RAG is an increasingly popular technique for allowing large language models (LLMs) to access and incorporate relevant data from external data sources, including domain-specific data or an organization's proprietary data, and so improve AI system outputs. Voyage AI, founded by Stanford University assistant professor Tengyu Ma in 2023 and based in Palo Alto, Calif., develops what MongoDB called "state-of-the-art" embedding and reranking models that enhance RAG data search and retrieval accuracy and improve the quality and reliability of AI application results. "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," according to the acquisition announcement. "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," Ma said in the announcement. "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," Ma said. Terms of MongoDB's acquisition of Voyage AI were not disclosed. Voyage AI raised $20 million in a Series A funding round in October 2024 led by CRV with investments from Wing VC, Conviction, Snowflake, Databricks, Pear VC, Tectonic Ventures, Mayfield Fund and Fusion Fund. At the time of the investment Databricks also announced a partnership with Voyage AI to add its rerank and embedding models to Databricks' Mosaic AI Model Serving, the generative AI platform developed by MosaicML, which Databricks acquired in June 2023 for $1.3 billion. MongoDB said Voyage AI's models will remain available through Voyage.ai, the AWS Marketplace and Azure Marketplace, "with further MongoDB integrations launching later this year," according to the announcement.

MongoDB acquires embedding model provider Voyage AI - SiliconANGLE

MongoDB Inc. today announced that it has acquired Voyage AI Inc., a startup with a series of artificial intelligence models for generating embeddings. The terms of the deal were not disclosed. Voyage AI previously raised $28 million in funding from Snowflake Inc., Databricks Inc. and other investors Nasdaq-listed MongoDB provides a popular document database of the same name. Traditional relational databases require all the records they store to follow the same format. MongoDB's document model has no such limitation, which simplifies application development. MongoDB provides its database in several editions including a managed, cloud-based version called MongoDB Atlas. The latter offering removes the need for customers to manage the infrastructure on which the database runs. It also eases other maintenance tasks, notably patching and the process of optimizing queries to lower their hardware usage. MongoDB Atlas provides features for, among other use cases, powering AI applications. The company's acquisition of Voyage AI is designed to enhance those capabilities. AI models don't process business files in their original format, but first turn them into embeddings. Those are mathematical structures that can store key details about a file and describe how it relates to the other records in a database. Embeddings are usually generated using AI models. Voyage AI has developed more than a half dozen AI models for generating embeddings. The flagship algorithm in the series, voyage-3-large, debuted last month. In terms of embedding quality, it promises to outperform competing models from OpenAI and Cohere Inc. by 9.7% and 20.7%, respectively. Voyage AI also offers several vertical-specific models. They're optimized to generate embeddings from code files, legal documents and financial data. Voyager AI offers its embedding generators alongside a collection of so-called rerankers. Those are AI models that reorganize search results to display the most relevant items first. When an AI application retrieves a collection of data points to answer a prompt, it uses a reranker to identify the most relevant data points. MongoDB plans to incorporate Voyage AI's models into MongoDB Atlas later this year. According to the company, the integration will enable developers to quickly turn their records into embeddings and save them in the database. AI applications built on Atlas will gain the ability to find the data most relevant to a given task using Voyage AI's rerankers. MongoDB sees the integration as a way to simplify the application development workflow. Often, software teams keep AI workloads' standard data and embeddings in two separate databases. Voyage AI's technology will make it more practical to store both data types in Atlas, which should simplify the coding workflow. "Instead of implementing workarounds or managing separate systems, developers can generate high-quality embeddings from real-time operational data, store vectors, perform semantic search, and refine results -- all within MongoDB," MongoDB Chief Executive Officer Dev Ittycheria wrote in a blog post. After integrating Voyage AI's models into Atlas, MongoDB plans to upgrade their capabilities. The company will add support for multimodal data such as images and videos. Additionally, MongoDB intends to introduce more industry-specific features for segments such as the legal and financial sectors.

MongoDB Acquires Voyage AI in a Bid to Redefine Databases in the AI Era

MongoDB plans to integrate Voyage AI's tech into its database and solve problems for developers building AI applications. MongoDB is a popular NoSQL source-available document database used by several global enterprises and Indian startups like Zepto. Organisations in India are increasingly seeking MongoDB's prowess to scale up their architecture to shift from traditional database platforms. They have also acquired Voyage AI, a company specialising in embedding models and rerankers for search and retrieval. Essentially, Voyage AI supports AI models in producing accurate and trustworthy responses. MongoDB plans to integrate Voyage AI's tech into its database and solve problems for developers building AI applications. The company states that it is challenging for developers to depend on a patchwork of various components when constructing AI-powered applications. Furthermore, the overall structure remains fragmented when a developer attempts to use AI-driven search and retrieval with databases, making it inefficient, costly, and cumbersome. And, with the acquisition, they claim that Voyage AI's connection to the database layer addresses this challenge. Dev Ittycheria, CEO of MongoDB, shed light on this in a statement, "MongoDB solves this challenge by making AI-powered search and retrieval native to the database. Instead of implementing workarounds or managing separate systems, developers can generate high-quality embeddings from real-time operational data, store vectors, perform semantic search, and refine results -- all within MongoDB." He also highlighted that this should eliminate complexity and deliver an accurate, fast, and seamless developer experience. He further mentions that they plan on integrating Voyage AI in three phases. The first phase will focus on making Voyage AI's embedding, multi-modal embedding, and retaking models widely available through current APIs and via AWS and Azure marketplaces. In the second phase, Voyage AI's capabilities will be embedded into MongoDB Atlas, with an auto-embedding service, followed by native reranking. Lastly, they aim to work on advancing AI-powered retrieval with enhanced multi-modal capabilities, with plans to introduce instruction-tuned models for developers. MongoDB believes this integration will improve developers' workflows when managing external embedding APIs and give businesses greater confidence in using AI for mission-critical use cases.

MongoDB Buys Voyage AI for $220 Million to Bolster AI Search

Database company MongoDB Inc. said it's acquiring Voyage AI for $220 million in a cash-and-stock deal to fast-track its ability to help its customers build artificial intelligence-powered applications. Through the deal, New York-based MongoDB aims to integrate Voyage's retrieval tools for higher-quality AI outputs with real-time operational data for businesses, allowing its customers to develop AI applications more easily and deploy them for higher-stakes uses. MongoDB helps manage data and develop applications for Google-parent Alphabet Inc., Microsoft Corp., Alteryx Inc., Amazon.com Inc., Deloitte LLP and International Business Machines Corp.

MongoDB acquires Voyage AI to reduce hallucinations in AI applications

MongoDB wants Voyage AI's embedding and reranking models to help enterprises with RAG in their AI applications. Database engine developer MongoDB has acquired Voyage AI in order to help enterprises reduce hallucinations in AI-powered applications. "With this acquisition, MongoDB will help deliver AI-powered, never-before-seen high quality outputs (via high quality data retrieval) as a fully formed database solution -- not with tacked on additions," the database developer firm said in a statement. Voyage AI develops embedding and reranking models used in retrieval-augmented generation (RAG). These models will help reduce hallucinations by enhancing vector search with new embeddings that better capture meaning and improving retrieval accuracy by refining search results to a particular query, MongoDB explained.

MongoDB Acquires Voyage AI to Combat Hallucinations | PYMNTS.com

The deal -- worth $220 million, according to a Monday (Feb. 24) Bloomberg report -- is designed to help MongoDB's customers build better AI-powered applications through "highly accurate and relevant information retrieval deeply integrated with operational data," according to a Monday press release. "AI-powered applications can address a broad range of complex use cases that traditional software cannot," the release said. "However, because AI models are probabilistic, they can hallucinate -- when a model generates false or misleading information." Low-quality or incorrect results can lead to "serious risks" in instances where accurate information is crucial, such as cancer screenings at hospitals or legal advice from law firms, meaning that AI applications are often limited to "mission-critical use cases," according to the release. Companies need "high-quality retrieval," ensuring that the most relevant information is pulled from their data with precision, per the release. "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," the release said. "Their models are trusted by leading AI innovators like Anthropic, LangChain, Harvey and Replit." Jenny Shern, general manager at robot builder NexCOBOT, told PYMNTS this month that humanoid robots face more complex challenges than industrial robots. "Traditional industrial robotic arms with vision systems primarily rely on preprogrammed instructions to execute tasks," she said. "This works well in factory environments where applications are repetitive and goal-oriented." However, "implementing humanoid robots into household settings is a more complex advancement because, unlike factories, household environments are highly dynamic, and tasks will vary significantly from one home to another," Shern said. When dealing with unpredictable settings, humanoid robots need AI to function effectively in everyday life because preprogrammed instructions aren't sufficient.

AI still has a hallucination problem: How MongoDB aims to solve it with advanced rerankers and embedding models

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More To get the best possible result from an AI query, organizations need the best possible data. The answer that many organizations have had to overcome that challenge is retrieval-augmented generation (RAG). With RAG, results are grounded in data from a database. As it turns out, though, not all RAG is the same, and actually optimizing a database for the best possible results can be challenging. Database vendor MongoDB is no stranger to the world of AI or RAG. The company's namesake database is already being used for RAG, and MongoDB has also launched AI applications development initiatives. While the company and its users -- such a medical giant Novo Nordisk -- have had success with gen AI, there is still more to be done. In particular, hallucination and accuracy continues to be an issue holding some organizations back from getting gen AI into production. To that end, MongoDB today announced the acquisition of privately-held Voyage AI, which develops advanced embedding and retrieval models. Voyage raised $20 million in funding in Oct. 2024 in a round supported by cloud data giant Snowflake. The acquisition will bring Voyage AI's expertise in embedding generation and reranking -- critical components for AI-powered search and retrieval -- directly into MongoDB's database platform. "Over the last year, and especially as organizations have tried to think about how they could build AI powered applications, it became increasingly clear that the quality and trust of the applications they build, or the lack thereof, was becoming one of the barriers for applying AI to mission critical use cases," MongoDB CPO Sahir Azam told VentureBeat. What are the challenges of hallucination? Doesn't RAG solve them? The basic idea behind RAG is that, instead of simply relying on a knowledge base from trained data, the gen AI engine can get grounded data from a database. Creating highly accurate RAG is quite complex, and there is still a potential risk for hallucinations -- a challenge faced by MongoDB and its users. While Azam declined to provide any specific example or incident where gen AI RAG failed a user, he did note that accuracy is always a concern. Improving accuracy and reducing hallucination involves multiple steps. The first is to improve the quality of retrieval (the 'R' in RAG). "In many cases, the retrieval quality is not good enough," Tengyu Ma, founder and CEO of Voyage AI, told VentureBeat. "In the retrieval step, if they are not retrieving relevant information, then the retrieval is not very useful, and the large language model (LLM) hallucinates because it has to guess some context." The Voyage AI models now part of MongoDB help improve RAG in a few key ways: MongoDB's competition MongoDB isn't the first or only vendor to recognize the need for and value of having highly optimized embedding and re-ranker technology. After all, that's one of the reasons Snowflake invested in Voyage AI and is using the company's models. It's important to note that, even after being acquired by MongoDB, Voyage AI's models will still be available to Snowflake and to Voyage AI's other users. The big difference is that Voyage AI will now be increasingly integrated into MongoDB's database platforms. Directly integrating advanced embedding models in a database is an approach taken by other rival database vendors, as well. Back in June 2024, DataStax announced its own RAGStack technology that combines advanced embedding and retrieval models. Azam argued that MongoDB is a bit different, though. For one, it is an operational database, as opposed to an analytical database. Also, as opposed to just providing insights and analysis, MongoDB helps power transactions and real-world operations. MongoDB is also what is known as a "document model database," which has a different structure than a traditional relational database. That structure does not rely on columns and tables, which are not particularly good at representing information about unstructured data (a critical element for AI applications). "We're the only database technology that combines the management of metadata about a customer's information, the operations and transactions, which is the heartbeat of what's happening in the business, as well as the foundation for retrieval -- all with a single system," said Azam. Why Voyage AI matters for agentic AI workflows The need for highly accurate embedding and retrieval models is being further accelerated by agentic AI. "Agentic AI still needs retrieval methods, because an agent cannot make decisions out of context," said Ma. "Sometimes, actually multiple retrieval components are used in even one decision." Ma noted that Voyage AI is currently working on specific models that are highly customized for agentic AI use cases. He explained that agentic AI can use different types of queries that can still benefit from more optimization. As gen AI increasingly moves into operational use cases, the need to remove the risk of hallucinations is clearly paramount. While MongoDB has had success with gen AI, Azam expects the integration of Voyage AI to open new mission critical use cases. "If we can now say, 'Hey, we can give you well north of 90% accuracy for your applications that today may only, in some cases, get to 30 or 60% accuracy for the results,' the aperture widens in terms of the types of opportunities people can apply AI to in their software applications," said Azam.