At their recent Evolve25 summit in New York, data and AI platform provider Cloudera made a pair of important announcements. First, they announced the integration of Dell ObjectScale with Cloudera. This advanced their joint ‘AI-in-a-Box’ offering and creating a comprehensive Private AI platform designed for scale, governance, and economic clarity. This collaboration provides joint customers with a fully validated and integrated data platform, allowing them to run all of Cloudera’s compute engines directly against Dell Technologies ObjectScale storage. Secondly, Cloudera announced the expansion of its Enterprise AI Ecosystem with new partnerships designed to deliver complete, production-ready AI solutions, and offer a complete suite of end-to-end solutions.
The AI market is rapidly evolving, and enterprises are moving quickly through new stages of AI maturity. As a result, one of the greatest challenges hindering enterprise AI success is the complexity around where data is located and how to access it. In fact, Cloudera’s latest survey report, The Evolution of AI: The State of Enterprise AI and Data Architecture, found that IT leaders still use a variety of architectures for storage: 63% of respondents said private cloud, 52% said public cloud, and 42% said data warehouses. Without the ability to securely and effectively manage 100% of enterprise data, in all forms, wherever it resides, the company says that it will be impossible for organizations to apply AI to workloads to make fully informed, strategic decisions.
To address these challenges, Cloudera collaborated with Dell Technologies to allow joint customers to store all their data–structured and unstructured–in one place and access it quickly and securely, with clear rules, security, and governance. In addition, the collaboration allows Cloudera users to leverage Dell ObjectScale as an S3-compatible object store for AL workloads:
Cloudera is helping enterprises navigate this transformation with its AI-powered lakehouse: a unified foundation that brings AI to data anywhere. With this approach, organizations can move beyond experimentation to embed AI directly into business operations, unlocking high-value use cases across customer experience, fraud detection, supply chain forecasting, IT operations, and compliance, all while maintaining governance, security, and architectural flexibility.
Cloudera’s end-to-end platform delivers both AI-ready data and AI agents that help to transform that data into intelligent actions. This tool has already enabled hundreds of Cloudera customers to shift from AI experimentation to having AI embedded throughout their functional teams. Cloudera’s ultimate goal is to help its customers become truly AI Native and leverage autonomous decision-making with minimal human intervention, supported by trusted, transparent systems.
To address these challenges, Cloudera collaborated with Dell Technologies to allow joint customers to store all their data – structured and unstructured – in one place and access it quickly and securely. As the only data and AI platform company bringing AI to data anywhere, Cloudera empowers enterprises to organize their data with clear rules, security, and governance. In addition, the collaboration allows Cloudera users to leverage Dell ObjectScale as an S3-compatible object store for AL workloads:
The combination of Dell Technologies’s leadership in AI infrastructure with Cloudera’s secure data platform and AI tools creates a complete Private AI system, offering significant business value. Companies can start using AI faster, achieve lower overall costs and trust their AI systems completely, which is crucial for highly regulated industries. This solution empowers enterprises to tackle the most pressing challenges of AI. It overcomes the hurdles of moving data, makes AI more affordable, simplifies managing AI tasks and deploys Private AI agents with trust and efficiency.
“Businesses need AI systems that can grow with them, keep data secure, and have clear, predictable costs,” said Abhas Ricky, Chief Strategy Officer, Cloudera. “Bringing Dell ObjectScale together with Cloudera enables organizations to industrialize AI use cases using secure data, deploy them efficiently, and create smart agents, all with predictable economics, and without hidden fees. This is the quickest and most reliable way for large companies to put AI to work and create intelligent agents. Cloudera is uniquely positioned to unify governed enterprise data with AI services on modern storage, creating the only Private AI platform that combines governance, performance, and clear economics at an industrial scale.”
Ricky said that having spoken to dozens of large Cloudera customers around their enterprise AI needs and requirements, he offered some insights about how customers can accelerate building AI applications at scale, at a price point of their choice, with the best TCO.
First, Cloudera Open Data enables customers to leverage 25 million terabytes of enterprise context and run LLMs with domain specific context, in a secure and governed fashion.
“You have to be able to TRUST your DATA to trust your hashtag,” Ricky emphasized.
GPU compute costs are an issue because hardware acceleration optimization has allowed customers to run scaled AI workloads on GPUs on private cloud or hybrid environments at a fraction of the cost, sometimes 35-50% cheaper!
“You want to bring the MODELS to the DATA and NOT the Data to the Models!” Ricky stressed.
Next, you need partnerships to enable the AI application lifecycle. If a company wants to deploy a support chatbot to decrease operational costs and improve customer experience, they can select the best foundational LLM for the job from Amazon or Hugging Face, then build the application on CML using frameworks like Flask Python, improve the accuracy of the chatbot responses by checking each question against embeddings stored in Pinecone’s vector database and enhance the question with data from Cloudera Open Data Lakehouse, and finally, deploy the application using CML’s containerized compute sessions powered by NVIDIA GPUs or Amazon Web Services – specialized hardware that improves inference performance while reducing costs.
“We will continue to add strategic partners and customers to the Ent AI ecosystem,” Ricky stated.
Key aspects of the system are Cloudera AI Workbench, a secure environment for building, training, and refining AI models using governed data, Cloudera Inference Service, which is a way to deploy and use these AI models efficiently and affordably at a large scale, and Cloudera Agent Studio, a tool to design and leverage smart AI agents that can automate tasks across business operations.
“This collaboration reflects our shared commitment to giving customers more flexibility in managing and scaling their data,” said Travis Vigil, senior vice president, ISG Product Management, Dell Technologies. “With Dell ObjectScale now integrated with Cloudera, we’re helping customers bring storage and AI closer together to empower smarter, faster decision-making that drives business growth.”
To accelerate this vision, Cloudera is expanding its Enterprise AI Ecosystem with four new partnerships.
ServiceNow’s AI Platform is an industry leader in enterprise workflow automation and AI-powered solutions. The future integration will feature the combined power of ServiceNow’s Workflow Data Fabric zero copy connector with Cloudera’s data foundation to allow organizations to securely access real-time enterprise data without duplication across IT, HR, finance, customer service, compliance and more. Customers can use predictive insights from Cloudera’s AI-powered lakehouse to prioritize tasks in ServiceNow workflows to automate approvals, proactively resolve issues, and streamline operations,
Fundamental provides a superhuman prediction engine for enterprise tabular data. Most enterprise challenges, including churn prediction, credit risk, fraud detection, and demand forecasting, are tabular prediction problems that have yet to be impacted by deep learning. Fundamental solves this gap with a foundation model that requires no parameter tuning or feature engineering. Pre-trained on diverse datasets, it immediately adapts to new data and delivers powerfully accurate predictions with just a single line of code.
“Fundamental makes predictive AI on tabular data simple and powerful,” said Jeremy Fraenkel, CEO and Founder of Fundamental. “Unlike foundation models trained on text or images, ours is purpose-built for the structured data that runs every enterprise, from transactions to customer records. Partnering with Cloudera, enterprises can now apply this predictive foundation model across their most critical datasets without the complexity of custom pipelines or tuning.”
Pulse provides the industry’s most accurate document processing engine, turning unstructured content – contracts, claims, reports, and more – into structured, LLM-ready data. By integrating Pulse into Cloudera’s AI-powered lakehouse, enterprises can automate data flows from document ingestion directly into ERP, CRM, and compliance systems. This collaboration ensures that previously siloed unstructured information can be brought into the same governed environment as structured data. This creates an end-to-end workflow: documents are ingested and processed by Pulse, structured and validated within Cloudera’s lakehouse, and then made immediately available for predictive modeling, generative AI agents, and workflow automation.
“Turning unstructured information into structured insights is one of the biggest challenges in enterprise AI,” said Sid Manchkanti, CEO and Co-founder, Pulse. “By integrating Pulse’s document processing capabilities into Cloudera’s platform, customers can unlock the full value of their documents, seamlessly feeding LLM-ready data into advanced AI workflows.”
Finally, Galileo.ai specializes in AI observability, helping enterprises validate, monitor, and maintain their AI systems in production. Their platform tracks model accuracy, drift, and reliability in real time, with dashboards and alerts purpose-built for large language models and agent-based systems. With Cloudera’s added capabilities, Galileo provides enterprises with a closed loop for trusted AI deployment. Data flows into the Cloudera lakehouse, models are trained and run on that data, and Galileo provides the visibility to ensure those models remain accurate, fair, and reliable as conditions change. Whether monitoring predictions generated by Fundamental’s tabular foundation model or insights extracted from Pulse’s document pipelines, Galileo ensures that every AI-driven workflow built on Cloudera stays compliant, transparent, and high-performing. This combination allows enterprises to not only deploy AI at scale, but to do so with the confidence that outcomes remain trustworthy over time.
“Trust and transparency are essential for AI in production,” said Vikram Chatterji, CEO and Co-founder, Galileo.ai. “With Cloudera, we’re equipping enterprises with the tools they need to test, evaluate, monitor, guardrail and maintain their AI applications at scale—ensuring accuracy and reliability even as data, models and conditions evolve.”
“The Enterprise AI Ecosystem has become a cornerstone of our strategy to help large enterprises navigate the complexities of AI adoption,” Ricky said. “Our newest partners bring specialized capabilities that directly address the biggest challenges our customers face today: operationalizing AI and agentic workflows at scale with ServiceNow, ensuring transparency, reliability, and accuracy with Galileo.ai and Pulse, and unlocking the next generation of AI on structured data with Fundamental.”
Existing members of Cloudera’s AI Ecosystem include NVIDIA, Amazon Web Services, Pinecone, Google Cloud, Anthropic, Snowflake, and CrewAI. Cloudera’s commitment to building a robust partner network is rooted in its foundational belief that no single vendor can solve all the intricate requirements of large-scale AI deployment. By fostering an open ecosystem, Cloudera empowers enterprises to choose the right tools and models for their specific use cases while maintaining control over their data and infrastructure