What is the reason this setting causes a mismatch between the configured queue_timeout in the Architect flow and the actual wait time observed in Genesys Cloud? Our AppFoundry integration pushes the timeout value via the Platform API, yet agents see calls dropped prematurely. The endpoint /v2/architect/flows accepts the payload without error. Genesys Docs. Is there a caching delay or a specific field mapping we are missing?
If you check the docs, they mention that predictive routing decisions are calculated before the queue timeout logic takes full effect, which often creates the illusion of a mismatch when the AppFoundry integration pushes values to the /v2/architect/flows endpoint. In my experience handling bulk exports for legal discovery, I see similar discrepancies when metadata timestamps do not align with the actual system event logs. The issue here is likely that the queue_timeout value in the JSON payload is being interpreted as a relative offset from the routing decision rather than an absolute duration from the call arrival. When you push the configuration via the Platform API, ensure the timeout is defined in milliseconds and that it exceeds the maximum expected wait time for the predictive queue. A common fix is to add a buffer of at least 5000ms to the configured timeout to account for network latency and processing overhead in the routing engine. You should also verify that the flow is not terminating the interaction due to a separate “no answer” or “agent unavailable” condition that overrides the queue timeout. Check the audit trail in the Recording API to see if the call was actually dropped by the system or if it was abandoned by the caller before the timeout expired. If the calls are being dropped prematurely, review the bulk export job configuration to ensure that the metadata is being committed correctly to the S3 bucket, as this can sometimes skew the observed wait times in the dashboard. The discrepancy often stems from the fact that the analytics endpoint is not built for real-time retrieval of queue metrics, so relying on the bulk export jobs for accurate data is always recommended for legal hold purposes. Ensure your legal hold settings are configured to capture all interaction data, including those that timeout, to maintain a complete chain of custody for any potential disputes.