How can we help?

Yes. Polyosync provides execution history for Collaboration Orchestration, helping authorized users review recorded runs and their outcomes. This is important because coordinating multiple AI agents should involve more than receiving a final AI-generated answer. Businesses also need visibility into whether an execution completed, encountered an error, or produced the expected outputs. What can I review? A recorded orchestration run can include its objective, status, start and completion timestamps, available results, and error information. Task-level results may also be available. This helps businesses understand the outcome of the overall collaboration and its participating tasks. Can I review earlier executions? Yes. Polyosync supports retrieving run history associated with a saved collaboration definition. This allows businesses to examine previous executions rather than relying only on the most recent result. Can I inspect individual task results? The orchestration API provides a business-facing representation of available task results. Depending on the execution, these may include task status, text, summary, or output information. Not every task necessarily produces all of these fields. What happens when a collaboration fails? The recorded run may contain a failure status and error information. Businesses can use this information to investigate the issue. Depending on the cause, it may be necessary to review task definitions, AI Employee configuration, knowledge, permissions, or connected services. Can every user access technical diagnostics? No. Polyosync distinguishes ordinary collaboration read access from elevated permissions required to view technical diagnostics. This helps restrict access to lower-level execution information. Does execution history guarantee the correctness of AI-generated conclusions? No. Execution history documents recorded operations and available results. Businesses should still verify important information and decisions. Why is this useful? A company using multiple AI agents needs to understand how collaborative activities perform over time. Polyosync combines multi-agent orchestration with execution history so businesses can review outcomes, investigate problems, and improve their configured collaborations.