
Tech • AI • Robotics
Warmwind OS has launched as a cloud-based AI automation platform that lets companies teach software agents by demonstration so they can carry out recurring work across real business applications, including systems without APIs.
Warmwind OS is positioned as an AI operating system for office automation rather than a replacement for Windows or macOS. Each AI worker gets its own cloud computer, applications and task environment, and can be monitored through browser, desktop and mobile interfaces. The system is built to run across Windows, Linux, Android and web apps, with work continuing even after a user shuts their own computer down.
The product focuses on recurring business processes rather than one-off chatbot queries. A worker can be assigned ongoing responsibilities such as customer support, invoice handling, lead qualification, website monitoring or document processing. Warmwind’s aim is to make the agent behave more like a digital employee with a standing job than an assistant waiting for prompts.
A central feature is a teaching mode in which a user performs a task once while explaining it by voice or text. In one example, the user opens Gmail, reviews a customer message, switches to SAP, searches for an order using the company name and order number, and uses the result to draft a reply. Warmwind then compiles that demonstration into a recurring workflow, shows the planned worklist and lets the user schedule it, such as 9 a.m. daily.
Warmwind’s workers are meant to use software the way people do: by looking at the screen, clicking, typing and navigating between applications. That matters in enterprises filled with legacy portals, ERP systems, supplier dashboards, accounting tools and custom internal software that may not expose clean APIs. The company also includes native app actions where faster direct methods are available, but the visual layer is the fallback that broadens coverage.
Warmwind is targeting business users who want to show a process rather than engineer one. More technical platforms offer highly configurable autonomous agents built around models, tools, APIs and custom infrastructure. Warmwind’s bet is that accountants, support managers and recruiters would rather teach a workflow directly than rely on developers to script and maintain automations.
Warmwind says general-purpose language models were not efficient enough for continuous computer use. It argues that visual understanding in office software remains difficult, that a single click through large models could take 30 to 60 seconds, and that operating such systems continuously could cost roughly €1,000 to €2,000 per hour. The company says it instead took inspiration from robotics and embodied AI, building a more specialized system for visual interaction and repetitive tasks.
The company does not present the workers as fully hands-off from day one. Users are expected to supervise early runs, provide missing information, interrupt jobs and add instructions when the system gets stuck. Warmwind says performance improves as workers see more examples, but the real test will be how well they handle messy exceptions such as large volumes of irregular customer emails.
Warmwind says companies can start with a single worker and scale to 10, 100 or 1,000 cloud workers. Because each worker runs on its own machine, users do not have to surrender control of their laptops or deal with agents taking over their cursor. The business pitch is broader than automating a browser task: it is to turn department workflows into fleets of persistent cloud workers.
Security is a major issue because the system may access company email, ERP software, invoices, customer data and passwords. Warmwind says user data is stored on isolated servers in Germany, each environment is separated, a built-in password manager is included, and users can export data locally and remove the cloud copy. The service launched globally on August 26 with pricing starting at €24 per week, support for multiple workers and an initial capacity of 10,000 users.
Warmwind is entering the automation market with a simpler pitch: teach AI workers by showing them the job inside the software companies already use. Its success will depend on whether that demonstration-based approach can handle real enterprise complexity at reliable cost and speed.
Explain this