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Autonomous Workflows in Polyosync allow businesses to assign an objective to an AI Workforce and have the platform coordinate the work required to pursue that objective. Unlike traditional automation, where each step is defined in advance, an Autonomous Workflow uses an AI orchestrator to evaluate progress, determine useful next tasks, and coordinate execution through available AI Employees and supported automations. This creates a more flexible approach to business operations. How do Autonomous Workflows work? A business defines an objective and selects an active AI Workforce. The orchestrator evaluates the objective and determines which tasks should be performed. Tasks can be delegated to AI Employees or executed through supported automations. As results become available, the orchestrator can evaluate progress and determine subsequent actions. Execution continues within configured operational limits and stops when the objective is verified as completed, execution limits are reached, or another condition prevents continuation. What makes this different from traditional automation? Traditional automation follows a configured sequence of steps. Autonomous Workflows allow the orchestrator to determine the next useful work based on the objective, available context, and execution results. This is particularly valuable when a business objective requires multiple activities that cannot all be predicted in advance. Does autonomous mean completely uncontrolled? No. Polyosync includes execution boundaries, task and iteration limits, AI cost budgets, approval handling, and execution history. Autonomy operates within these controls. Who is this designed for? Autonomous Workflows are particularly relevant to organizations that want to coordinate multi-step business objectives across AI Employees. The capability is presented within Polyosync's Enterprise environment. The objective is to help businesses move from automating individual activities toward coordinating more complex outcomes through an AI Workforce.