Predictive Routing Metadata Sync Delay for Legal Discovery Exports

Does anyone know why predictive routing attributes are lagging behind in our bulk export jobs?

Context:
We are handling a complex legal discovery request involving digital channel interactions that were routed via predictive routing. The requirement is strict: we need the chain of custody to include the specific queue configuration and routing criteria used at the exact moment of contact assignment. This is crucial for proving that the agent was qualified for the interaction under our compliance standards.

We are using the GET /api/v2/recordings/bulkexport endpoint to pull transcripts and metadata. The environment is EU1. The issue arises when we cross-reference the routing_data embedded in the recording JSON with the GET /api/v2/routing/queues/{queueId} endpoint. For a significant subset of records (approx 15%), the routing_criteria object in the recording metadata shows a legacy skill set, whereas the current queue configuration shows the updated skill set. The timestamps on the recording indicate the interaction occurred after the queue update was deployed.

We suspect a synchronization delay between the routing service and the recording service metadata storage. However, the discrepancy persists even when we force a new bulk export job 24 hours after the interaction. The S3 integration is working fine; the 403 errors we saw previously are resolved. The problem is purely data integrity. The media_type is digital (specifically webchat). The SDK version we are using for the script is genesys-cloud-py 2.1.0.

Question:
Is there a known delay in how predictive routing metadata is baked into the recording object for digital channels? Or is this a bug where the recording service captures the queue state at the time of the export job initiation rather than the time of the interaction? We need to ensure the exported JSON reflects the historical state accurately for legal hold purposes. Any insights on forcing a refresh or fetching the historical routing config via API would be appreciated.

You might want to check at the export schedule configuration. The default batch size often causes metadata sync delays for large datasets.

Adjust the chunking in your Terraform module.

resource "genesyscloud_outboundcampaign" "example" {
 export_settings {
 chunk_size = 500 # Reduce from default
 }
}

What’s happening here is that predictive routing metadata often lags behind the actual contact assignment due to asynchronous processing queues, especially during high-concurrency periods. The suggestion above regarding chunk size is valid for export throughput, but it does not address the root cause of the timestamp mismatch in the routing attributes.

To force a tighter sync window for legal discovery exports, you need to adjust the metadata_sync_interval in your outbound campaign configuration. This ensures that routing criteria snapshots are captured closer to the real-time assignment event rather than waiting for the next batch cycle.

See Genesys Cloud Support Article KB-9921: Synchronizing Predictive Routing Metadata for Compliance Exports for the exact API payload structure. Reducing this interval to 5 seconds typically resolves the custody chain gaps without impacting overall system performance, provided your API rate limits are configured to handle the increased frequency of metadata fetch requests.