New integrations with leading enterprise applications and partnerships with deployment specialists aim to help organisations adopt AI workflows while maintaining security, governance and control.
Cloudflare is expanding the partner ecosystem for its Cloudflare OS AI workspace, adding integrations with major enterprise applications and deployment partners to help organisations move AI initiatives from experimentation into everyday business operations.
The announcement includes integrations with Asana, Box, Canva, ClickHouse, GitHub, Gong and Notion, alongside partnerships with professional services and deployment teams EPAM, HappyCog and Towards AI. The initiative is designed to help enterprises connect AI-powered workflows to the systems they already use, while giving administrators greater control over data access, deployment and security.
“AI tools shouldn’t force companies to choose between moving fast and staying secure.”
— Matthew Prince, Co-founder and CEO, Cloudflare
The expansion addresses a growing enterprise dilemma. Employees are increasingly adopting AI tools to accelerate work, but unmanaged usage can expose sensitive information, introduce unreviewed AI-generated code and increase model costs without adequate oversight. Organisations must balance productivity gains with the need for security and governance.
Cloudflare OS is designed to provide a managed environment where employees can describe an automation or application they need and use the platform to build and deploy it. The workspace can connect these tools to enterprise systems while limiting access to the data required for specific tasks. It runs on Cloudflare’s infrastructure rather than employee laptops, giving security teams greater visibility into how applications operate.
The platform also incorporates Cloudflare’s AI Gateway, which allows organisations to select models for different workloads and manage AI usage and associated costs.
Matthew Prince, Co-founder and CEO of Cloudflare, said the company initially built Cloudflare OS for its own teams and is now extending the experience to organisations using widely deployed enterprise platforms. The objective, he said, is to provide a secure, company-aware AI workspace without requiring every deployment to become a major engineering project.
The application integrations extend AI workflows into existing business processes. Asana can help teams track tasks and identify blockers, while Box brings enterprise content into AI-powered workflows under existing security and access controls. Canva enables agents to find and transform designs, and ClickHouse supports automated workflows using live data.
Gong connects its revenue intelligence with other enterprise systems, enabling teams to build agents around sales processes and customer interactions. Notion brings organisational knowledge into workflows that span multiple applications. GitHub is also among the announced integrations.
Cloudflare is relying on deployment partners to help organisations translate their processes into practical AI applications. EPAM, HappyCog and Towards AI will support adoption, implementation and the development of agents connected to enterprise tools.
Matt Weinberg, Co-founder and President of Happy Cog, said security and governance must be built into the deployment of autonomous agents and internal AI tools. He highlighted Cloudflare’s Zero Trust network and capability-based security model as foundations for controlled enterprise execution.
Assel Kashkenbayeva, Chief Deployment Officer at Towards AI, said deployment teams can help organisations move beyond pilots by embedding AI into important business processes and building on workflows proven in production.
The expanded ecosystem reflects a broader shift in enterprise AI adoption. As organisations seek measurable productivity gains, the challenge is no longer simply providing access to models. It is connecting AI to business data and applications while preserving security, controlling costs and ensuring that automation operates within defined boundaries.
Cloudflare’s strategy is to bring those capabilities into a common workspace, supported by integrations and deployment expertise, so enterprises can introduce AI into existing workflows without assembling every component themselves.
