Is it possible to

Architect & Flows
1
  • Is it possible to inject BYOC trunk failover metrics directly into Genesys Cloud AI Bot analytics?
  • Current setup uses 15 BYOC trunks across APAC regions with complex SIP registration logic.
  • Need to correlate carrier-specific 488 errors with bot abandonment rates.
  • Standard WEM exports lack granular SIP signaling data for outbound routing.
  • Looking for API endpoints or custom fields to bridge this gap.
2

It depends, but generally native injection isn’t supported. The gap between SIP signaling and Genesys Cloud analytics requires a pipeline.

Is it possible to inject BYOC trunk failover metrics directly into Genesys Cloud AI Bot analytics?

Direct API mapping for 488 errors to bot abandonment is not available via standard WEM exports. The system treats these as separate domains. A common fix is using a custom pipeline.

  1. Export SIP logs via the BYOC provider’s API or syslog.
  2. Ingest into a time-series DB (InfluxDB/Prometheus).
  3. Use Genesys Cloud Data Connect to export bot metrics.
  4. Join datasets in BI tool (PowerBI/Tableau) by timestamp and region.

Terraform can automate the Data Connect configuration:

resource "genesyscloud_dataconnect_archive" "bot_metrics" {
 name = "Bot-Abandonment-Export"
 description = "For correlation with SIP logs"
 schedule {
 frequency = "daily"
 }
}

This bridges the data gap without modifying core platform logic.

3

It depends, but generally injecting raw SIP signaling data directly into the Genesys Cloud AI Bot analytics dashboard is not supported out-of-the-box. The platform separates telephony infrastructure metrics from conversational AI performance data to maintain system stability and clear data lineage. However, correlating carrier-specific 488 errors with bot abandonment requires a custom integration pipeline rather than a native feature.

A more viable approach involves using Genesys Cloud Data Actions to push relevant conversation metadata to ServiceNow or an intermediate data warehouse, where it can be joined with BYOC trunk logs. You can configure a Data Action to trigger on conversation end, capturing the routing.skill.id and any custom attributes related to the initial channel type.

{
 "fields": {
 "conversation_id": "{{conversation.id}}",
 "abandon_reason": "{{conversation.stats.abandon_reason}}",
 "initial_channel": "{{routing.skill.id}}"
 }
}

This payload can be sent via a webhook to ServiceNow, where a scheduled job correlates the initial_channel with external BYOC error logs. This method allows for granular analysis without overloading the Genesys Cloud API. Refer to the Data Actions documentation for detailed configuration steps: https://developer.genesys.cloud/docs/api/v2/data/actions.

Note that this approach requires careful mapping of skill IDs to trunk groups to ensure accurate correlation. Also, consider the rate limits on Data Actions to avoid throttling during peak call volumes. This setup provides a robust way to bridge the gap between SIP signaling and bot analytics, offering deeper insights into how carrier issues impact customer interactions.