使用 AI agents 发现数据访问中一个熟悉的障碍的竞赛
竞速将AI agents投入生产的企业正在发现基于角色的访问控制，而不是模型选择，决定这些agents是否可以被信任。 推论成本上升、隐私担忧和主权要求也使更多的AI工作量回到公司数据中心。
这种转变有利于多年来管理大规模敏感数据的公司。 Cloudera Inc. 正在Cloudera Anywhere Cloud上下注，这是一个混合数据和AI平台，覆盖公共云层和立体环境。 据Cloudera公司首席产品官Leo Brunnick(图片)说
”Brunnick 称。 “你们要分开的东西，首先是你们独特的数据。 你独特的数据和独特的过程，你的阿尔法——是什么让你成为一个企业。”
Brunnick与CUBE的丽贝卡·奈特和保罗·吉林在EVOLVE26,SiliconANGLE Media的直播工作室的独家广播中交谈。 他们讨论了AI agents为何必须遵循用户的数据权限，将AI工作量推回公司数据中心的力量，以及包装蓝图和伙伴关系如何简化私人AI的采用。 (* 下文披露。 )
为什么现在基于角色的访问控制延伸到AI agents
客户很少为了自己而想要一个新的平台，因此Cloudera正在出售特定问题的解决方案。 其包装的蓝图和与Mistral AI SAS,Nvidia公司和Vast Data Inc.的扩大伙伴关系针对的是私家AI使用的案件，如欺诈侦测。 Mistral专攻开量模型，用于孕期孕育，同时也借给Cloudera一些它在AI市场上所缺少的东西。
“云霄已经具备能力。 我们所没有的，人们不认为我们是AI公司，“Mistral允许我们做的是略微提高我们的能力，并天文上提高我们的信誉。”
治理是一项艰巨的工作。 Agents需要看到整个公司的数据是有用的，所以每个人都必须知道谁是用户以及该用户被允许看到什么，布伦尼克解释了。
“agent需要能够看到公司的一切，agent需要知道你是谁，你的权限是什么，”Brunnick 称。 “这就是他们需要做的
SiliconANGLE及CUBE报导EVOLVE26:
(*披露：CUBE是EVOLVE26 2026赛事的付费媒体合作伙伴。 CUBE活动报道的发起人Cloudera和其他赞助者对CUBE或SiliconANGLE上的内容都没有编辑控制。 ).
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The race to deploy AI agents finds a familiar hurdle in data access
Enterprises racing to put AI agents into production are discovering that role-based access control, not model choice, decides whether those agents can be trusted. Rising inference costs, privacy worries and sovereignty demands are also pulling more AI workloads back inside corporate data centers.
That shift favors companies that have spent years governing sensitive data at scale. Cloudera Inc. is betting on Cloudera Anywhere Cloud, a hybrid data and AI platform that spans public clouds and on-premises environments. The company has long been strong on governance, security and scalability but weaker on usability, a gap the new platform was built to close, according to Leo Brunnick (pictured), chief product officer of Cloudera.
“It turns out that the model is ultimately not going to be what separates your success from your competitor’s success,” Brunnick said. “The things that are going to separate you are, number one, your unique data. Your unique data and your unique processes, your alpha — what makes you a business.”
Brunnick spoke with theCUBE’s Rebecca Knight and Paul Gillin at EVOLVE26, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed why AI agents must follow users’ data permissions, the forces pushing AI workloads back into corporate data centers and how packaged blueprints and partnerships can simplify private AI adoption. (* Disclosure below.)
Why role-based access control now extends to AI agents
Customers rarely want a new platform for its own sake, so Cloudera is selling solutions to specific problems instead. Its packaged blueprints and expanded partnerships with Mistral AI SAS, Nvidia Corp. and Vast Data Inc. target private AI use cases such as fraud detection. Mistral, which specializes in open-weight models for on-prem inferencing, also lends Cloudera something it has lacked in the AI market.
“Cloudera already had the capabilities. What we don’t have is a lot of credibility around AI. People don’t think of us as an AI company,” Brunnick said. “What Mistral is allowing us to do is increase our capabilities slightly and increase our credibility astronomically.”
The harder work lies in governance. Agents need to see data across the entire company to be useful, so each one must know who the user is and what that user is permitted to see, Brunnick explained.
“Since the agent needs to be able to see everything in the company, the agent needs to know who you are and what your permissions are,” Brunnick said. “That’s what they need to get right so they can actually put stuff into production that doesn’t blow up on them.”
Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of EVOLVE26:
(* Disclosure: TheCUBE is a paid media partner for the EVOLVE26 2026 event. Neither Cloudera, the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)
Photo: SiliconANGLE
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