Optimized Workforce Learning — multi-agent assistance for real-world task automation.
OWL (Optimized Workforce Learning) is a multi-agent framework for general assistance in real-world task automation. Built on top of the CAMEL framework, it orchestrates specialized agent teams to handle complex, multi-step tasks. Features include dynamic role assignment, tool use coordination, and learning from task outcomes. Designed for practical automation scenarios like research, data processing, and business workflows.