Cloudera expands Enterprise AI Ecosystem to power AI factories Anywhere. Expanding the AI ecosystem with Mistral AI, VAST Data, Neo4j and Cartesia brings greater choice across enterprise knowledge, models, voice, and infrastructure. Cloudera today announced the expansion of its Enterprise AI Ecosystem at EVOLVE26 New York. Building on its Enterprise AI Ecosystem from 2024 and 2025, the expansion strengthens Cloudera Anywhere Cloud as the foundation for enterprise AI factories: environments that continuously turn governed data into insight and autonomous action. As enterprises move from asking AI questions to entrusting agents with business outcomes, each layer of the architecture matters. Agents need connected knowledge to understand business context, models suited to each task, responsive interfaces, and infrastructure that keeps data flowing. Anywhere Cloud will bring these capabilities together through a consistent operating model across public cloud, private cloud, and on-premises environments - giving customers greater freedom to meet performance, cost, and sovereignty requirements. "The next competitive advantage will come from how effectively enterprises turn their own knowledge into action," said Abhas Ricky, Chief Business Officer and GM, Applied AI at Cloudera. "Our ambition is to make every enterprise an AI factory, with the freedom to choose its models, retain control of its data, and improve the economics of every workload. Anywhere Cloud and our expanding ecosystem will connect the capabilities to make that possible - from the first insight to the millionth agentic action." Connected knowledge makes agentic action more reliable. Neo4j adds knowledge graphs and semantic context, helping agents query relationships across enterprise data and understand how customers, products, transactions, and business processes connect. Combined with Cloudera's governed data foundation, this supports the progression from finding information to reasoning over it and taking informed action. "Our partnership with Cloudera helps organizations create a shared knowledge layer across enterprise data in public and private cloud environments, delivering the critical connection between relational data and deep semantic context. The Cloudera Open Data Lakehouse, in combination with Neo4j's Graph Intelligence Platform, allows organizations to query massive datasets, uncover hidden relationships, and power next-generation enterprise AI safely across any cloud or on-premises environment," said Sudhir Hasbe, President & Chief Product Officer at Neo4j. Sovereign voice brings those capabilities into everyday interactions. Cartesia expands model choice with speech generation and transcription for voice agents operating within customer-controlled environments. Cartesia reports sub-90-millisecond speech-generation latency; its Sonic-3.6 model ranked first on both Artificial Analysis speech arena leaderboards at launch. These capabilities support natural, responsive interactions while helping enterprises retain control of sensitive conversations. "Voice is becoming the primary interface for AI, and the enterprises that stand to gain the most are often those bound by the strictest data sovereignty and governance requirements," said Karan Goel, CEO and Co-Founder of Cartesia. "Together with Cloudera, we're enabling the world's most regulated organizations to deploy real-time voice agents at scale while retaining complete control over their data." Specialised intelligence broadens what the factory can produce. Cloudera's previously announced strategic partnership with Mistral remains central to its sovereign inference strategy. Mistral's expanding portfolio includes the announced 1.05-trillion-parameter Large 4 model, Timestral forecasting models, and Robostral for embodied navigation. Its engineering collaboration with NVIDIA and scientific AI work with CERN further demonstrate the breadth of specialised intelligence emerging beyond conversational AI. Model choice allows enterprises to match capability, latency, and compute requirements to each workload. "As enterprises transition to production-ready agentic workflows, maintaining control over sensitive data and infrastructure is non-negotiable," said Marjorie Janiewicz, CRO of Mistral. "Integrating Mistral's frontier models and products with Cloudera's hybrid data platform will allow organizations to build, train, and deploy custom intelligence on their own proprietary data, with full governance across any environment." High-performance data infrastructure keeps the factory productive. The previously announced VAST Data partnership addresses GPU starvation by supplying accelerators with high-throughput, low-latency data. VAST's storage architecture supports Cloudera's containerized data services, helping improve data delivery, GPU utilization, and the performance of AI and analytics workloads across Anywhere Cloud. "Most enterprises already have the data they need for AI. The challenge is unlocking the value in data to create a continuous pipeline of AI inference, fine-tuning, and data analysis to build the next generation of intelligent applications," said Jeff Denworth, Co-Founder at VAST Data. "Together, Cloudera and VAST are helping customers build AI factories that connect data, intelligence, and infrastructure into a single operational platform for AI across hybrid environments." Together, these partnerships extend choice across the AI stack. Through an expanding portfolio of joint solutions and validated reference architectures, Cloudera aims to reduce integration effort, improve total cost of ownership, and make hybrid and sovereign AI easier to put into production.

Cloudera expands AI ecosystem with Neo4j & Cartesia. Wed, 28th Oct 2026 (Today) Cloudera has expanded its Enterprise AI Ecosystem, adding Neo4j and Cartesia to partners including Mistral AI and VAST Data. The expansion adds technologies spanning knowledge graphs, AI models, voice tools and data infrastructure to Cloudera's Anywhere Cloud platform. The additions are intended to support customers running AI workloads across public cloud, private cloud and on-premises environments. Cloudera said the ecosystem is part of its push to help businesses use governed data for AI systems and software agents. Neo4j joins the programme with its knowledge graph technology. Cloudera said this will help customers connect business data with semantic context, allowing AI systems to query relationships across customers, products, transactions and business processes. The focus on connected data reflects a broader industry effort to improve AI reliability by grounding outputs in structured enterprise information. Cloudera is positioning knowledge graphs as a layer for reasoning over internal data, rather than simply retrieving information. "Our partnership with Cloudera helps organisations create a shared knowledge layer across enterprise data in public and private cloud environments, delivering the critical connection between relational data and deep semantic context. The Cloudera Open Data Lakehouse, in combination with Neo4j's Graph Intelligence Platform, allows organisations to query massive datasets, uncover hidden relationships, and power next-generation enterprise AI safely across any cloud or on-premises environment," said Sudhir Hasbe, President & Chief Product Officer, Neo4j. Cartesia brings speech generation and transcription models to the ecosystem. Cloudera said the tools are aimed at voice agents used in customer-controlled environments, particularly for organisations with strict data-handling and sovereignty requirements. Cartesia reports sub-90-millisecond speech-generation latency, while its Sonic-3.6 model ranked first on two Artificial Analysis speech arena leaderboards at launch, according to Cloudera. The company said those features are designed to support more natural voice interactions while keeping sensitive conversations under customer control. "Voice is becoming the primary interface for AI, and the enterprises that stand to gain the most are often those bound by the strictest data sovereignty and governance requirements," said Karan Goel, Chief Executive Officer and Co-Founder, Cartesia. "Together with Cloudera, we're enabling the world's most regulated organisations to deploy real-time voice agents at scale while retaining complete control over their data." Existing partners The expansion also builds on earlier partnerships with Mistral AI and VAST Data. Cloudera said Mistral remains central to its strategy for sovereign inference, with support for a range of models for different workloads. Mistral's portfolio, as outlined by Cloudera, includes the Large 4 model with 1.05 trillion parameters, Timestral forecasting models and Robostral for embodied navigation. Cloudera said model choice matters as companies try to match AI systems to different latency and compute demands. "As enterprises transition to production-ready agentic workflows, maintaining control over sensitive data and infrastructure is non-negotiable," said Marjorie Janiewicz, Chief Revenue Officer, Mistral. "Integrating Mistral's frontier models and products with Cloudera's hybrid data platform will allow organisations to build, train, and deploy custom intelligence on their own proprietary data, with full governance across any environment." VAST Data remains the infrastructure-focused partner in the group. Cloudera said the relationship is aimed at addressing data-delivery bottlenecks for GPU-based AI workloads, particularly where storage throughput and latency constrain model training, inference and analytics. Cloudera said VAST's storage architecture supports its containerised data services and can help improve GPU utilisation and data delivery across hybrid environments. That reflects a wider concern in AI deployments over the cost of underused accelerator hardware. "Most enterprises already have the data they need for AI. The challenge is unlocking the value in data to create a continuous pipeline of AI inference, fine-tuning, and data analysis to build the next generation of intelligent applications," said Jeff Denworth, Co-Founder, VAST Data. "Together, Cloudera and VAST are helping customers build AI factories that connect data, intelligence, and infrastructure into a single operational platform for AI across hybrid environments." Hybrid focus Cloudera is framing the expanded ecosystem around customer choice in deployment models and suppliers. It said its Anywhere Cloud approach is designed to provide a consistent operating model across public cloud, private cloud and on-premises environments, with attention to cost, performance and data sovereignty. Abhas Ricky, Chief Business Officer and GM, Applied AI, Cloudera, said the company sees competitive advantage shifting towards businesses that can use their own data more effectively in AI systems. "The next competitive advantage will come from how effectively enterprises turn their own knowledge into action," said Ricky. "Our ambition is to make every enterprise an AI factory, with the freedom to choose its models, retain control of its data, and improve the economics of every workload. Anywhere Cloud and our expanding ecosystem will connect the capabilities to make that possible-from the first insight to the millionth agentic action."

Cloudera launches Cloudera Blueprints, bringing NVIDIA Agent Toolkit to enterprise data anywhere. Cloudera | Published 28 Oct 2026 New ready-to-deploy AI solutions help enterprises accelerate the journey from prototype to production with built-in data management, security, and governance across cloud, data centres, and the edge Australia and New Zealand - October 28, 2026 - Cloudera, the only company bringing AI to data anywhere, today announced the launch of Cloudera Blueprints, a new portfolio of ready-to-deploy AI solutions designed to help enterprises accelerate the development and deployment of AI applications using their own data. Building on its existing Accelerators for ML Projects (AMPs), the expanded portfolio introduces NVIDIA AI Blueprints, built with NVIDIA Agent Toolkit on Cloudera, combining NVIDIA's reference AI workflows with Cloudera's enterprise data management, security, and governance capabilities to help organisations move AI use cases from proof of concept to production. As enterprises scale AI, accessing, preparing, and governing the data needed for production remains a challenge. This is especially true in regulated industries, where sensitive data spans multiple environments and cannot easily be moved. While AI reference workflows can accelerate initial development, integrating these applications with enterprise data and meeting production requirements involves significant work. Cloudera Blueprints address these challenges with preconfigured AI solutions that run directly on Cloudera AI, connecting proven AI workflows with enterprise data and infrastructure. Organisations can build and deploy applications on the same platform across public clouds, on-premises data centres, and the edge, bringing AI directly to their data while maintaining consistent security, governance, and control. "Enterprises are eager to move beyond AI experimentation, but turning promising prototypes into production-ready applications remains a challenge, particularly when data is spread across complex environments," said Leo Brunnick, Chief Product Officer, Cloudera. "With Cloudera Blueprints, we're closing that gap by combining proven AI workflows from NVIDIA with the data management, security, and governance capabilities enterprises need to deploy AI at scale. By bringing AI directly to their data, wherever it resides, we're helping organisations accelerate time to value and turn AI innovation into real business impact." Accelerating AI innovation across industries. Cloudera Blueprints will soon leverage NVIDIA AI Blueprints on Cloudera, targeting high-value AI applications across financial services, healthcare, telecommunications, and other industries: * Build Your Own Transaction Foundation Model: Help financial institutions develop transaction-based foundation models to improve fraud detection, risk assessment, and personalised customer experiences. * Ambient Healthcare Agents: Automate clinical documentation by transforming patient-provider conversations into structured clinical notes, while supporting patient intake, scheduling, and enquiries. * AI Agent for Telecom Network Configuration Planning: Help telecommunications providers optimise network performance with AI agents that recommend, apply, and validate radio access network configurations using historical and real-time data. * Synthetic Video Detection: Support organisations in identifying AI-generated video content to strengthen digital trust, identity verification, and fraud prevention. Additional NVIDIA AI Blueprints will be incorporated into the Cloudera Blueprints portfolio based on evolving industry requirements and customer demand. Bringing nvidia-accelerated AI to enterprise data anywhere. Cloudera Blueprints extend NVIDIA's AI reference workflows with the enterprise capabilities required to deploy and scale AI applications in real-world environments. By combining Cloudera's hybrid data and AI platform with NVIDIA-accelerated computing, organisations benefit from: * A faster path from prototype to production: Ready-to-deploy solutions simplify production deployment by integrating AI workflows with data ingestion, data engineering, security, and governance. * AI wherever enterprise data resides: Deploy AI applications across public cloud, on-premises data centres, and the edge without requiring sensitive or regulated data to be relocated, while maintaining consistent governance, lineage, and security. * End-to-end NVIDIA acceleration: Leverage NVIDIA NIM microservices and NVIDIA Nemotron models through Cloudera AI Inference, alongside NVIDIA cuDF for Apache Spark in Cloudera Data Engineering, to accelerate workloads from data preparation through inference. * Flexibility through open standards: Maintain choice across AI models, infrastructure, and deployment environments through an open-source foundation while reducing vendor lock-in. "NVIDIA and Cloudera share a commitment to helping enterprises accelerate AI adoption and realise the full value of their investments," said Pat Lee, Vice President, Strategic Enterprise Partnerships, NVIDIA. "By combining NVIDIA's accelerated computing and AI software stack with Cloudera's hybrid data platform, we're making it easier for organisations to deploy AI wherever their data resides, whether in the cloud, on premises, or at the edge." The introduction of Cloudera Blueprints further expands Cloudera and NVIDIA's ongoing collaboration to help enterprises operationalise AI at scale. By combining NVIDIA's AI innovation with Cloudera's ability to securely manage and access data across hybrid environments, the companies are helping organisations accelerate time to value and turn AI investments into measurable business outcomes. Cloudera Blueprints will be showcased at EVOLVE26 New York, Cloudera's annual data and AI conference, today.