Can I see what tasks and activities my AI Employees have completed?
Polyosync provides execution history and activity information for supported AI-driven business operations.
This helps businesses review what has happened when AI Employees participate in configured workflows, automations, collaborations, and business processes.
Why is execution history important?
A conversation with an AI assistant may explain what the assistant intends to do.
An execution record provides a different type of information: it helps document the actual operation and its recorded outcome.
For businesses using AI agents to support real operational activities, this distinction matters.
What activities can I review?
Polyosync includes history capabilities across several operational modules.
Autonomous Workflows support structured AI-driven activities.
Automations support configured automated actions and triggers.
AI Collaboration supports interactions and cooperation between AI Employees.
Business Processes provide execution records associated with configured processes.
The information available depends on the module and the type of execution.
What information might an execution record contain?
Depending on the relevant module, records may include execution status, timestamps, results, events, or error information.
For example, a Business Process execution can provide details about its recorded status and available execution events.
This allows authorized users to investigate a process rather than relying only on a conversational description.
Can I verify that an AI Employee completed an action?
The relevant execution record can help verify the outcome recorded by Polyosync.
For actions involving external services, businesses may also need to verify the final result in the connected system.
An AI Employee saying that a task is complete should not be treated as sufficient proof that every external action succeeded.
Can this support accountability?
Yes.
Reviewable execution records help businesses understand which supported activities ran and what results were recorded.
This is useful when investigating operational problems, improving processes, or reviewing AI-assisted work.
Polyosync is designed to support businesses that want AI agents to participate in real workflows while maintaining visibility into the operations performed through the platform.