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Yes. Polyosync includes AI Collaboration records that help authorized business users review supported interactions between AI Employees. This is important because businesses need visibility into how their AI agents cooperate, not just the final answer produced by an individual AI assistant. What information can be reviewed? For recorded collaborations, Polyosync can provide information about the AI Employee that initiated the request and the AI Employee that received it. Available records can also include the delegated task, reason for collaboration, execution status, result, and relevant timestamps. This helps businesses understand which AI Employees participated in an activity and why assistance was requested. Can I see which AI Employee delegated a task? Yes. Supported collaboration records distinguish between the source AI Employee and the target AI Employee. The source is the employee initiating the collaboration request. The target is the employee receiving the delegated work. Can I see the reason for collaboration? Yes, where the reason has been recorded. This can help explain why an AI Employee requested another employee's expertise during its work. Can I review the outcome? Recorded collaborations can contain a result and completion information. Where an execution fails, relevant error information may also be available. The detail available depends on the collaboration and its recorded execution data. Can I see collaboration chains? Polyosync's collaboration records support chain and execution relationship information. This can help represent situations in which collaboration involves connected execution steps rather than a single isolated exchange. Can collaboration require approval? The collaboration system supports approval-related states for applicable requests. Where approval is required, a collaboration may remain pending until the relevant authorization is provided. This is particularly important for businesses that want AI agents to cooperate while retaining control over selected activities. Why does this matter? Multi-agent collaboration becomes more useful to businesses when the activity can be reviewed. Polyosync combines Dynamic Collaboration with recorded execution information, helping organizations understand how AI Employees contribute to shared tasks and investigate problems when necessary.