Cloudera, the only company bringing AI to data anywhere, announced the expansion of Cloudera AI Inference and Cloudera Data Warehouse with Trino to on-premises environments, empowering customers to harness advanced AI and analytics directly from within their data centers. The company also announced enhanced AI and analytics capabilities within Cloudera Data Visualization, streamlining AI workflows across cloud, edge, and data center environments.
As enterprises move from AI experimentation to production, the conversation has evolved: it’s no longer just about where data is stored, but about providing AI with secure, reliable, and governed access to that data, wherever it resides. According to Cloudera’s recent report, The State of Enterprise AI and Data Architecture, nearly half of companies store their data in a data warehouse. By guaranteeing that AI applications can access this data securely, organizations can extract meaningful insights without transferring sensitive information outside of protected environments. This approach helps to minimize security risks, limits compliance exposure, and streamlines operations.
With Cloudera AI Inference, powered by NVIDIA technology, now available on premises, organizations can deploy and scale any AI model, including the latest NVIDIA Nemotron open models—from LLMs, fraud detection, computer vision, voice, and more—directly within their data centers. Accelerated by the NVIDIA AI stack, by NVIDIA Blackwell GPUs, NVIDIA Dynamo- Triton Inference Server, and NVIDIA NIM microservices for high-performance, scalable model serving, Cloudera AI Inference enables secure, governed deployment of AI at enterprise scale, delivering superior cost-efficiency and predictable economics. This offers superior cost-efficiency and predictable economics by avoiding the volatile costs of the cloud, organizations gain full control over latency, compliance, and data privacy while ensuring that once AI moves into steady production, long-term costs remain lower and easier to manage.
Cloudera Data Warehouse with Trino – now available in data center environments – enables centralized security, governance, and observability across the entire data estate while accelerating access to insights. With integrated AI-powered analytics and visualization, enterprises can turn complex data into actionable outcomes without compromising security, compliance, or operational control.
The enhancements to Cloudera Data Visualization empower organizations to gain richer insights and streamline AI-driven workflows in the data center and beyond. These include:
- AI annotation: Instantly generate summaries and contextual insights for charts and visuals, without manual writing, enhancing clarity across your data estate
- Resilient AI features: Robust features now handle transient issues and provide detailed usage analytics for easy monitoring and optimization
- AI query logging and traceability: Each AI query logs message ID, timestamp, and question for traceability, streamlining transparency and issue resolution
- Simplified admin management: Easily assign admin roles using updated configuration parameters to streamline SSO-based setup by removing hard-coded credentials and manual user promotion
“These advancements provide our customers with a superior level of control and flexibility,” said Mr. Leo Brunnick, Chief Product Officer at Cloudera. “With Cloudera AI Inference, Cloudera Data Warehouse with Trino, and Cloudera Data Visualization all accessible in the data center, organizations can securely deploy AI and analytics exactly where their most critical data resides. This means enterprises can drive innovation and derive insights without compromising on data security, compliance, or operational efficiency.”
“The value of enterprise data is realized when AI can be securely and flexibly deployed where that data lives,” said Mr. Pat Lee, vice president, strategic enterprise partnerships, NVIDIA. “Our collaboration with Cloudera enables customers to deploy and scale AI inference using NVIDIA Blackwell GPUs, Dynamo-Triton and NIM microservices, delivering control, predictable economics, and data-center efficiency.”
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