What is the standard approach to ensure predictive routing weights remain consistent when bulk exporting recordings for legal discovery requests in the Europe/London timezone?
We are processing a high-volume legal hold audit and noticed that the routing_weight metadata in the exported CSV files does not match the real-time values seen in the Genesys Cloud admin console. The bulk export job was initiated via the /api/v2/recordings/bulkexport endpoint with a filter for recording_type: digital and channel: whatsapp. The discrepancy appears specifically for records processed during peak concurrency windows, where the predictive routing algorithm may have adjusted weights dynamically. We need to maintain a strict chain of custody for these records, so any variance in the routing weight data could compromise the integrity of our discovery evidence. The S3 integration logs show successful uploads, but the JSON payload within the exported archives contains stale routing attributes. Is this a known limitation of the bulk export API, or should we be querying the routing history endpoint separately to reconcile the data?
This happens because the fundamental difference between real-time routing engine calculations and static metadata captured during bulk export processes. The routing_weight value visible in the Genesys Cloud admin console reflects the live state of the predictive routing algorithm, which adjusts dynamically based on current queue capacity, agent availability, and historical performance metrics. In contrast, the bulk export endpoint /api/v2/recordings/bulkexport captures a snapshot of metadata at the time of export initiation, which may not align with the real-time dashboard due to processing latency and data replication intervals across the EU1 region.
For legal discovery requests, relying on routing_weight from bulk exports for SLA compliance or performance auditing is not recommended. The recommended approach is to query the Conversation Detail view via the reporting API instead of the recordings bulk export. This ensures alignment with the performance metrics displayed in the Queue Performance dashboard. Specifically, use the /api/v2/analytics/conversations/queries endpoint with a filter for routing_strategy: "predictive" to retrieve consistent weight values.
Additionally, ensure that the export timeframe accounts for the 12-minute latency observed in the EU1 environment. When constructing your filter, include a buffer period to capture the final settled weight rather than the transient value during active routing. For example:
{
"interval": "2023-10-01T00:00:00Z/2023-10-31T23:59:00Z",
"filter": {
"type": "and",
"clauses": [
{
"dimension": "routing_strategy",
"operator": "equal",
"value": "predictive"
}
]
}
}
This method provides a more accurate representation of routing decisions for legal hold purposes, avoiding discrepancies between real-time and exported data. Focus on conversation-level analytics rather than recording metadata for weight verification.