Traditional operating systems (OS) were built to manage hardware, files, apps, and users on a device, but Cloudflare says the agentic AI era requires a whole new format.
The company this week announced .
“Cloudflare OS isn’t a traditional desktop OS,” said , Durable Objects, and Access, the company’s zero trust network access (ZTNA) tool that verifies every user and request. Agents start with zero permissions by default and are only granted access to tools required for a specific task. Organizations configure their own Access policies, models, branding, skills, and integrations, Kozlov explained.
Governed connectors known as gatekeepers give admins control over what AI can see, what it can change, and when the system needs human sign-off. They can also control budgets, set rate limits, and delegate tasks to different models.
“Because .
“This very much is not Windows, macOS, or Linux, and it isn’t an operating system by its common definition,” he said. “But Cloudflare’s use of this terminology implies familiarity to enterprise IT buyers.”
This makes for an easier discussion as enterprises struggle to understand how to best incorporate AI-related platforms and workflows into infrastructure that wasn’t initially designed for it.
Microsoft has marketed the combination of its Azure, Entra, Fabric, Windows, and Microsoft 365 offerings as an operating system of sorts, but hasn’t pulled all the pieces into a common brand, Levy said. And Google’s Gemini, Workspace, Vertex AI, and Cloud Run are “circling similar territory.”
But, he noted, Cloudflare OS is “more cohesively bundled” and infrastructure-focused, offering a single pane of glass platform for buyers worried about stitching together otherwise disparate AI-aware networking pieces. The company recognizes that AI introduces new architectural realities such as inference and model routing “over and above” traditional OS core competencies.
“While competing offerings generally leave the infrastructure heavy lifting to enterprise decision-makers, Cloudflare is marketing itself as a single-source vendor, which potentially frees IT planners from having to integrate all the AI pieces on their own,” Levy said.
An infrastructure-first, application-agnostic approach means Cloudflare OS can coexist with whatever AI applications already exist in an enterprise, he said. It will “play nice” with OpenAI, Anthropic, Google, Microsoft, Meta, or open source layers, allowing employees to begin working in familiar workflows after sign-in.
“Its open-source architecture also minimizes the potential for vendor lock-in as enterprises gradually figure out how to evolve their stacks to align with new AI-era realities,” Levy said.
Managing identities and budgets for both humans and AI
As AI agents emerge across the enterprise, tracking their use can be challenging, causing problems from both a security and a spend standpoint. Along with Cloudflare OS, the company has launched a way to address this issue with its new , explain in a blog post. Anything above 2x an account’s 95th percentile is a “strong candidate for anomalous behavior.”
For instance, one Cloudflare customer had an employee who left a rogue AI session running, generating a $30K bill. “User Insights helped them identify the problem and shut off access before the problem was further exacerbated,” Kozlov said.
Cloudflare is also building prompt classification functionality that sorts requests into categories such as coding or writing. This can help enterprises understand what AI is being used for.
“Once business traffic is separated from everything else, personal use becomes visible,” the project managers explained. “From the outside, someone running a side hustle on company time and someone quietly moving data out through a model look the same. Telling them apart is central to catching insider risk.”
Looking at the bigger picture
Identity-Aware AI Gateway and AI Spend address the visibility problem that has dogged so many recent AI deployments where enterprises failed to monitor usage, Levy noted. Projects “crashed and burned” as users unwittingly blew through token allocations.
These platforms provide single-point visibility into what is being used, how it’s being used, and where the potential lies for raising the productivity bar, he said. They overlay with existing models; in doing so, they enhance security with more precise control over resource allocations, and via automated anonymization protocols that prevent inadvertent sharing of sensitive data.
Ultimately, he said, vendors who free IT from having to independently assemble the pieces of their own AI implementations, and who assist them with answers to AI-specific questions, “will gain advantage over vendors that aren’t looking at the bigger picture.
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