Tech News
Hewlett Packard Enterprise and NVIDIA Announce ‘NVIDIA AI Computing by HPE’ to Accelerate Generative AI Industrial Revolution
Hewlett Packard Enterprise and NVIDIA announced NVIDIA AI Computing by HPE, a portfolio of co-developed AI solutions and joint go-to-market integrations that enable enterprises to accelerate adoption of generative AI.
Among the portfolio’s key offerings is HPE Private Cloud AI, a first-of-its-kind solution that provides the deepest integration to date of NVIDIA AI computing, networking and software with HPE’s AI storage, compute and the HPE GreenLake cloud. The offering enables enterprises of every size to gain an energy-efficient, fast, and flexible path for sustainably developing and deploying generative AI applications. Powered by the new OpsRamp AI copilot that helps IT operations improve workload and IT efficiency, HPE Private Cloud AI includes a self-service cloud experience with full lifecycle management and is available in four right-sized configurations to support a broad range of AI workloads and use cases.
All NVIDIA AI Computing by HPE offerings and services will be available through a joint go-to-market strategy that spans sales teams and channel partners, training and a global network of system integrators — including Deloitte, HCLTech, Infosys, TCS and Wipro — that can help enterprises across a variety of industries run complex AI workloads.
Announced during the HPE Discover keynote by HPE President and CEO Antonio Neri, who was joined by NVIDIA founder and CEO Jensen Huang, NVIDIA AI Computing by HPE marks the expansion of a decades-long partnership and reflects the substantial commitment of time and resources from each company.
“Generative AI holds immense potential for enterprise transformation, but the complexities of fragmented AI technology contain too many risks and barriers that hamper large-scale enterprise adoption and can jeopardize a company’s most valuable asset – its proprietary data,” said Neri. “To unleash the immense potential of generative AI in the enterprise, HPE and NVIDIA co-developed a turnkey private cloud for AI that will enable enterprises to focus their resources on developing new AI use cases that can boost productivity and unlock new revenue streams”.
“Generative AI and accelerated computing are fueling a fundamental transformation as every industry races to join the industrial revolution,” said Huang. “Never before have NVIDIA and HPE integrated our technologies so deeply – combining the entire NVIDIA AI computing stack along with HPE’s private cloud technology – to equip enterprise clients and AI professionals with the most advanced computing infrastructure and services to expand the frontier of AI.”
HPE and NVIDIA co-developed Private Cloud AI portfolio
HPE Private Cloud AI delivers a unique, cloud-based experience to accelerate innovation and return on investment while managing enterprise risk from AI. The solution offers:
● Support for inference, fine-tuning and RAG AI workloads that utilize proprietary data.
● Enterprise control for data privacy, security, transparency, and governance requirements.
● Cloud experience with ITOps and AIOps capabilities to increase productivity.
● Fast path to consume flexibly to meet future AI opportunities and growth.
Curated AI and data software stack in HPE Private Cloud AI
The foundation of the AI and data software stack starts with the NVIDIA AI Enterprise software platform, which includes NVIDIA NIM inference microservices.
NVIDIA AI Enterprise accelerates data science pipelines and streamlines development and deployment of production-grade copilots and other GenAI applications. Included with NVIDIA AI Enterprise, NVIDIA NIM delivers easy-to-use microservices for optimized AI model inferencing offering a smooth transition from prototype to secure deployment of AI models in a variety of use cases.
Complementing NVIDIA AI Enterprise and NVIDIA NIM, HPE AI Essentials software delivers a ready to run set of curated AI and data foundation tools with a unified control plane that provide adaptable solutions, ongoing enterprise support, and trusted AI services, such as data and model compliance and extensible features that ensure AI pipelines are in compliance, explainable and reproducible throughout the AI lifecycle.
To deliver optimal performance for the AI and data software stack, HPE Private Cloud AI delivers a fully integrated AI infrastructure stack that includes NVIDIA Spectrum-X Ethernet networking, HPE GreenLake for File Storage and HPE ProLiant servers with support for NVIDIA L40S, NVIDIA H100 NVL Tensor Core GPUs and the NVIDIA GH200 NVL2 platform.
Cloud experience enabled by HPE GreenLake cloud
HPE Private Cloud AI offers a self-service cloud experience enabled by HPE GreenLake cloud. Through a single, platform-based control plane, HPE Greenlake cloud services provide manageability and observability to automate, orchestrate and manage endpoints, workloads, and data across hybrid environments. This includes sustainability metrics for workloads and endpoints.
HPE GreenLake cloud and OpsRamp AI infrastructure observability and copilot assistant
OpsRamp’s IT operations are integrated with HPE GreenLake cloud to deliver observability and AIOps to all HPE products and services. OpsRamp now provides observability for the end- to- end NVIDIA accelerated computing stack, including NVIDIA NIM and AI software, NVIDIA Tensor Core GPUs and AI clusters as well as NVIDIA Quantum InfiniBand and NVIDIA Spectrum Ethernet switches. IT administrators can gain insights to identify anomalies and monitor their AI infrastructure and workloads across hybrid, multi-cloud environments.
The new OpsRamp operations copilot utilizes NVIDIA’s accelerated computing platform to analyze large datasets for insights with a conversational assistant, boosting productivity for operations management. OpsRamp will also integrate with CrowdStrike APIs so customers can see a unified service map view of endpoint security across their entire infrastructure and applications.
Accelerate time to value with AI – expanded collaboration with global system integrators
To advance the time to value for enterprises to develop industry-focused AI solutions and use cases with clear business benefits, Deloitte, HCLTech, Infosys, TCS and WIPRO announced their support of the NVIDIA AI Computing by HPE portfolio and HPE Private Cloud AI as part of their strategic AI solutions and services.
HPE adds support for NVIDIA’s latest GPUs, CPUs and Superchips
● HPE Cray XD670 supports eight NVIDIA H200 NVL Tensor Core GPUs and is ideal for LLM builders.
● HPE ProLiant DL384 Gen12 server with NVIDIA GH200 NVL2 is ideal for LLM consumers using larger models or RAG.
● HPE ProLiant DL380a Gen12 server support for up to eight NVIDIA H200 NVL Tensor Core GPUs is ideal for LLM users looking for flexibility to scale their GenAI workloads.
● HPE will be time-to-market to support the NVIDIA GB200 NVL72 / NVL2, as well as the new NVIDIA Blackwell, NVIDIA Rubin and NVIDIA Vera architectures.
High-density file storage certified for NVIDIA DGX BasePOD and NVIDIA OVX systems
HPE GreenLake for File Storage has achieved NVIDIA DGX BasePOD certification and NVIDIA OVX™ storage validation, providing customers with a proven enterprise file storage solution for accelerating AI, GenAI and GPU-intensive workloads at scale. HPE will be a time-to-market partner on upcoming NVIDIA reference architecture storage certification programs.
Availability
● HPE Private Cloud AI is expected to be generally available in the fall.
● HPE ProLiant DL380a Gen12 server with NVIDIA H200 NVL Tensor Core GPUs is expected to be generally available in the fall.
● HPE ProLiant DL384 Gen12 server with dual NVIDIA GH200 NVL2 is expected to be generally available in the fall.
● HPE Cray XD670 server with NVIDIA H200 NVL is expected to be generally available in the summer.
Tech News
Cloudera and Mistral Partner to Bring Specialized, Sovereign Intelligence to Enterprise Data

Cloudera, the only company bringing AI to data anywhere, and Mistral, a global frontier AI lab, today announced a landmark strategic partnership to bring secure, sovereign AI directly to enterprise data wherever it resides.
Cloudera and Mistral will combine Cloudera’s hybrid data and AI platform with Mistral’s sovereign AI models to give enterprises a secure path to build, customize, and run AI using their own private data. The collaboration will enable organizations to bring intelligence directly to their data across cloud, on-premises, edge, sovereign, and air-gapped environments—without requiring sensitive information to leave their control.
For enterprises managing the world’s largest and most sensitive data estates, this approach provides greater control, choice, and flexibility over how and where AI runs. Organizations can run inference privately, customize AI using proprietary data, and deploy AI applications within their existing security and governance boundaries, while gaining greater control over the economics of AI at scale.
“Enterprise AI is entering a new phase where organizations need more than access to powerful models, they need the freedom to unlock specialized intelligence using their data, on their terms,” said Abhas Ricky, Chief Business Officer & GM, Applied AI at Cloudera. “Together with Mistral, we are giving enterprises the ability to run AI where their data lives, customize it with their own intellectual property, and maintain control over their data, infrastructure, and economics. That combination of intelligence and control is essential to moving AI from experimentation into production.”
Bringing Intelligence to the Data
For enterprises operating in highly regulated and data-intensive industries, moving sensitive or proprietary information to external AI services can introduce regulatory, security, and operational challenges.
Cloudera and Mistral are addressing these challenges by bringing secure, sovereign AI directly to the enterprise data perimeter.
Mistral’s suite of frontier models and tools will be integrated with Cloudera’s hybrid data and AI platform, enabling customers to run their own custom AI models and applications across 30 exabytes of data. Enterprises will have the deployment flexibility across public, private, on-premises, and fully air-gapped environments, while maintaining consistent governance and control over their context.
The partnership will span Mistral’s broad portfolio of frontier AI models and tools, including reasoning, chat, coding, document intelligence, and voice, giving Cloudera customers greater choice in how they apply AI to their enterprise data.
By enabling organizations to run inference within their own environments, the collaboration also gives customers greater flexibility over the economics of AI. Enterprises can choose the deployment model and infrastructure that best fit their workloads rather than depending exclusively on public API consumption models as AI usage scales.
From Private Inference to Proprietary Intelligence
Through the integration of Mistral Forge, a system for enterprises to build frontier-grade AI models grounded in their proprietary knowledge, organizations utilizing Cloudera’s platform will be able to customize and train models against large volumes of private enterprise data within controlled environments. For enterprises with petabytes of proprietary information, this creates an opportunity to transform decades of institutional data and domain expertise into differentiated AI while maintaining ownership and sovereignty over both the data and resulting intelligence.
Developers and practitioners will also be able to securely build AI-powered experiences using private enterprise data within local environments—from conversational access to governed data to AI-assisted software development and agentic workflows—without exposing sensitive business context or intellectual property to external environments.
Cloudera and Mistral also intend to collaborate on the next generation of AI at the edge, bringing increasingly capable inference closer to where enterprise data is created. This will enable organizations to explore intelligent applications across disconnected, latency-sensitive and resource-constrained environments where relying on centralized cloud infrastructure is not practical.
“Our mission is to make frontier AI available to enterprises without requiring them to give up control over their data, infrastructure, or intellectual property,” said Kamal Brar, SVP of Partnerships and Alliances at Mistral. “Cloudera manages some of the world’s most valuable enterprise data estates, making this partnership a powerful opportunity to bring our technology directly to where that data lives. Together, we can give customers the ability to build AI that reflects their own data and expertise and deploy it securely wherever their business requires.”
Expanding Choice for Enterprise AI
The partnership also expands the Cloudera Enterprise AI Ecosystem, through which Cloudera works with leading AI models, infrastructure, application, and technology providers to give customers flexibility in how they build and deploy enterprise AI.
Mistral adds a significant new dimension to that ecosystem by enabling customers to access and customize its models and AI capabilities directly alongside their governed enterprise data. The partnership reinforces both Cloudera’s and Mistral’s commitment to an open approach to enterprise AI, giving customers choice across models, infrastructure, and deployment environments rather than locking their data or AI strategy into a single technology stack.
The joint Cloudera and Mistral solutions will be available through Cloudera’s enterprise sales team and partner ecosystem, with additional integrations and capabilities rolling out over time.
Spotlight
New Cequence & EMA Research: 94% of Enterprises Trust Their AI Agents Aren’t Over-Provisioned. Only 33% Actually Enforce It.
Nearly every enterprise believes its AI agents are properly scoped. Only a third have actually made sure of it.
Today, new research from Cequence Security, the leader in application, API, and agentic AI protection, and Enterprise Management Associates (EMA) found that 94% of enterprise IT and security leaders are confident their AI agents do not have more access than they need, yet only 33% actually provision agents with least-privilege access. The remaining two-thirds run on broad standing permissions that are reviewed periodically, rarely reviewed, or never reviewed at all.
That gap between confidence and practice is already showing up in production, not a theoretical risk, but as incidents enterprises are living with right now. Among the organizations surveyed:
- 65% have experienced an AI agent take an action outside its intended scope, including 29% with measurable business impact, including data exposure, financial loss, operational disruption, or reputational damage. Another 36% caught a near-miss before it caused damage.

- Only 32% can detect and contain an out-of-scope agent action within minutes through automated means; 55% need hours and manual steps to respond.
- In approximately 4% of organizations surveyed, the first sign of trouble came from a customer or outside partner, not an internal system.
The findings point to one clear story. Governance has not kept pace with the speed of agentic AI deployment, and that gap is showing up at every stage of the agent lifecycle, from how agents are provisioned, to how their actions are authorized, to how they are decommissioned once a pilot ends. Other key findings from the report include:
Enterprises Have Moved Past the Pilot Stage
The scale of deployment makes the gap more urgent. 46% of organizations report they are already scaling agentic AI across multiple departments and production workflows, and 79% are running generative and agentic AI simultaneously. Further, more than 92% report an increase in AI and bot-driven traffic targeting customer-facing applications and APIs.
Authorization is Checked at the Wrong Time, Or Not At All
That governance gap extends to how access is enforced in the moment an agent acts. Only 34% of organizations evaluate an AI agent’s authorization at the moment it attempts a specific action. The majority rely on periodic policy reviews or standing permissions set once at provisioning and never revisited, meaning an agent’s access can quietly outlive the task it was originally granted for, and keep working long after anyone signed off on it.
Abandoned Pilots Are Leaving Live Credentials Behind
Additionally, there’s an increasing risk in how enterprises manage agents that don’t make it to production. 31% of agentic AI pilots have been paused indefinitely, discontinued, or abandoned. Many were real deployments with real system access and credentials that were never cleaned up. Every abandoned pilot with live credentials is exposure nobody is actively watching.
External Connectivity Carries the Same Risk
14% of organizations allow AI agents to connect to outside tools and data sources via the Model Context Protocol (MCP) without restriction. Among the majority who do limit those connections to an approved list, fewer than half, just 49%, have a dedicated team actively maintaining and auditing that list on a regular basis.
Christopher M. Steffen, CISSP, CISA, VP of Research at EMA, said: “This research shows enterprises have moved well past experimentation with agentic AI right into production, and governance has not kept pace with that shift. The gap isn’t a lack of awareness; most organizations have policies in place and express real confidence in them. The gap is between what’s written down and what’s enforced when an agent takes an action nobody approved. That disconnect shows up most clearly in how organizations authorize agent actions and monitor them once they’re live, and it’s the reason incidents are happening at a rate the industry hasn’t fully reckoned with.”
Shreyans Mehta, Co-founder and CTO at Cequence, said: “The number that jumped out to me is the 92% being confident in their governance frameworks. Confidence like that is a trap; it’s exactly why organizations stop looking for problems, stop investing in monitoring, and let authorization checks lapse until an incident forces the conversation. This is the exact blind spot Cequence is built to close, giving security teams real-time visibility into what AI agents are actually doing and enforcing authorization at the moment an agent acts, not after the fact.”
Tech News
Anomali to Address the Next Phase of AI-Led Cyber Defense at GISEC 2026
Anomali, the leading global Managed Intelligence and Agentic SOC platform, announced its participation at GISEC Global 2026, taking place through 16-18 September at Dubai Exhibition Centre (DEC), Expo City.
The company’s discussions at GISEC will center on Autonomous SOC with Governed AI, Agentic AI, Actionable Threat Intelligence and Unified Security Data Lake capabilities that are changing the manner in which security teams investigate threats, manage workflows and make decisions.
Samer Jadallah, Vice President, Middle East & Africa at Anomali, will represent the company at GISEC and will focus on the growing impact of AI on both attackers and defenders, emerging shifts in the threat landscape, including the need to counter CEO impersonation attacks as well as key challenges facing modern security teams. He will also highlight AI’s role is helping organizations respond more effectively to evolving threats, Anomali’s commitment to the region and ongoing product innovation and plans to expand adoption of the Anomali platform across global enterprises and government organizations.
A key focus at this year’s event will be the changing nature of cyberattacks. As threat actors promptly adopt AI to scale campaigns and further accelerate attacks, security operations centers (SOC) are under growing pressure to process rising volumes of alerts with limited resources. To help with this, Anomali will demonstrate how AI can support analysts in multiple ways like surfacing higher- value insights, reducing manual effort and enabling quicker, informed responses.
Visitors can find Anomali at Booth E156 and Booth A80.
- Event: GISEC Global 2026
- Booths: E156 and A80
- Location: Dubai Exhibition Centre (DEC), Expo City
- Dates: 16 th to 18 September 2026
- Time: 9:00 am to 5:00 pm GST
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