Configuration is broken for some reason…
We are attempting to integrate real-time sentiment analysis into our existing BYOC trunk infrastructure in AP-Southeast-1. The goal is to stream the audio from the 15 active SIP trunks directly to a custom AI service for immediate analysis, bypassing standard WEM recording latency. However, the integration is failing consistently when the Architect flow attempts to initiate the audio stream.
The environment consists of Genesys Cloud Edge in Singapore, with outbound routing configured to prefer our primary carrier for cost efficiency, falling back to secondary carriers only on 408 timeouts. The issue arises specifically when the bot skill invokes the /api/v2/voice/bots/{botId}/sessions/{sessionId}/stream endpoint. Instead of establishing a WebSocket connection for the audio payload, the request returns a 502 Bad Gateway error within 200ms. This behavior is observed across all 15 trunks, suggesting the issue is not carrier-specific but rather related to how the platform handles media bridging for BYOC traffic in this region.
Here is the relevant error response from the logs:
{
"message": "Bad Gateway",
"status": 502,
"details": "Upstream server timed out while attempting to bridge media stream for BYOC trunk trunk-ap-se-1-prod-01"
}
We have verified that the SIP registration status for all trunks is healthy, and manual test calls complete successfully with full media. The problem seems isolated to the programmatic streaming capability via the API. We are using the latest version of the Genesys Cloud SDK for Python (3.1.2) and have confirmed that the OAuth tokens have the necessary bot:read and voice:stream scopes.
Has anyone successfully implemented real-time audio streaming for BYOC trunks in the AP-Southeast-1 region? We suspect this might be related to the specific media server topology in Singapore or a known limitation with how BYOC media is handled during bot interactions. Any insights into whether this is a configuration error on our end or a platform-side limitation would be greatly appreciated. We need to determine if we should pivot to using WEM recordings for post-call analysis instead.