The News: In June, Cloudera announced that it was acquiring Verta to accelerate customers’ Generative AI application development and implementation ROI. See the “Cloudera Makes Bold Bet on Strategic Acquisition of Verta’s Operational AI Platform” press release for additional details.
AI in Context: Cloudera Accelerates AI ROI with Verta Acquisition
Analyst Take: It’s a natural progression for a company that started in the days of big data, perhaps moved to analytics, then data warehouses, lakes, and lakehouses, to now be building AI on its platforms. Not content with only being part of the infrastructure, such a company tries to evolve into a full-stack provider of the development tools and management for AI, specifically Generative AI. Over the last several years, Cloudera has been strongly and deliberately moving in this direction. With its acquisition of Verta, Cloudera has fleshed out its portfolio in essential ways. Verta’s tools make it faster to experiment with and develop applications in a bring-your-own-model manner. The additions speed up the time to deployment, allowing customers to reach AI ROI faster.
Cloudera’s History
Cloudera was founded in Silicon Valley in 2007. I first became aware of it as a provider of Apache Hadoop, a big data toolset that implemented the map-reduce architecture across networked computers. After several investment rounds, including $740 million from Intel, the company went public in 2017 via an IPO. The following year, it merged with Hortonworks, another company built primarily on Apache open-source data software. In 2021, Cloudera was acquired and taken private by global investment firm KKR & Co. Inc. and private equity company Clayton, Dubilier & Rice.
Cloudera’s data products run across private on-premise data centers and public clouds, including AWS, Microsoft Azure, Google Cloud, and Alibaba Cloud. Cloudera Machine Learning sits on top of its Open Data Lakehouse. Above this, Cloudera supports Generative AI models from open and proprietary foundation models. In a private briefing, the company stressed that it is not creating new foundation models nor monetizing the simple hosting of those models. All products and services are in support of the final Enterprise AI RAG (Retrieval Augmented Generation) applications and optimizing their use.
Verta and Its AI Pedigree
Verta addresses the DevOps aspect of moving AI models into production. Based on research at MIT, the company provides products to deploy, version, track, and audit models. It manages and accelerates the life cycle process from experimentation to prototype to general availability.
Verta provides a model repository to centralize and manage all AI assets through its AI Hub. Among other solutions, the AI Hub enables more effective governance and responses to the increasing regulation around the use of AI. For example, the AI Hub allows Verta’s customers to strictly adhere to the recent EU AI Act and audit requirements.
The Value of the Cloudera and Verta Union
Verta significantly extends the Cloudera stack and its value to its partners and customers. From top to bottom, I expect Cloudera + Verta to fully integrate the combined features to enable complete and managed Enterprise AI applications. Building on the Cloudera infrastructure, Verta provides capabilities for the responsible use of AI, including transparency, privacy, and safety.
Verta claims one can make a custom RAG application with no code in five minutes. Given Cloudera’s existing RAG capabilities, this is a powerful addition for increasing developer efficiency. Whether it is five minutes or thirty, the speed-up encourages iterative experimentation, yielding better solutions. Decreasing development time also allows time for more applications. Either way, earlier ROI for higher-quality Enterprise AI is the result.
Cloudera plans to increase the use of Generative AI within its products and tools. After all, if the features are good enough to sell to others, they should be employed within the vendor’s own offerings.
Key Takeaway
The Verta acquisition by Cloudera should result in a more complete and tighter integrated stack for data management and Enterprise AI. Verta has state-of-the-art bona fides from its start at MIT and a deep and experienced staff. Cloudera’s earned knowledge, extensive partner and customer ecosystem, and 25 exabytes of global data under management are ideal for extending Verta’s existing customer base. Together, customers will get better tools and faster results for their data and AI use cases.
Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold an equity position in any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole.
Other Insights from The Futurum Group:
Trusted Data: The Difference Maker – Six Five – On the Road with Cloudera
Cloudera’s Enterprise AI Ecosystem – Six Five – On the Road
Cloudera’s AI Ecosystem Advancements – Six Five – On the Road
Author Information
Dr. Bob Sutor has been a technical leader and executive in the IT industry for over 40 years. Bob’s industry role is to advance quantum and AI technologies by building strong business, partner, technical, and educational ecosystems. The singular goal is to evolve quantum and AI to help solve some of the critical computational problems facing society today. Bob is widely quoted in the press, delivers conference keynotes, and works with industry analysts and investors to accelerate understanding and adoption of quantum technologies. Bob is the Vice President and Practice Lead for Emerging Technologies at The Futurum Group. He helps clients understand sophisticated technologies in order to make the best use of them for success in their organizations and industries. He is also an Adjunct Professor in the Department of Computer Science and Engineering at the University at Buffalo, New York, USA. More than two decades of Bob’s career were spent in IBM Research in New York. During his time there, he worked on or led efforts in symbolic mathematical computation, optimization, AI, blockchain, and quantum computing. He was also an executive on the software side of the IBM business in areas including middleware, software on Linux, mobile, open source, and emerging industry standards. He was the Vice President of Corporate Development and, later, Chief Quantum Advocate, at Infleqtion, a quantum computing and quantum sensing company based in Boulder, Colorado USA. Bob is a theoretical mathematician by training, has a Ph.D. from Princeton University, and an undergraduate degree from Harvard College.
He’s the author of a book about quantum computing called Dancing with Qubits, which was published in 2019, with the Second Edition released in March 2024. He is also the author of the 2021 book Dancing with Python, an introduction to Python coding for classical and quantum computing. Areas in which he’s worked: quantum computing, AI, blockchain, mathematics and mathematical software, Linux, open source, standards management, product management and marketing, computer algebra, and web standards.
