We are facing a critical data integrity issue regarding the chain of custody for legal discovery requests. Our team is responsible for exporting recording metadata and audio files for all customer interactions, including those handled by our AI Bot flows.
Our environment is Genesys Cloud (London region). We are using the Recording API v2 to trigger bulk export jobs. Specifically, we are filtering by conversationType equal to voice and applying date ranges that cover the last 30 days.
The problem is that conversations where the initial leg was handled by an AI Bot (via Architect bot flow) are not appearing in the bulk export results, even though we can see them in the Admin UI under Conversations. When we manually check the specific conversation IDs in the UI, we see that the recording exists and is accessible. However, when we query the bulk export job status via /api/v2/recordings/jobs/{jobId}, the completedCount for these specific bot-handled conversations is zero, and they are effectively skipped.
We suspect this might be related to how the metadata is tagged for bot-initiated versus agent-handled legs, or perhaps a delay in the recording archive index. We need to ensure that all voice interactions, regardless of whether they were resolved by a bot or transferred to an agent, are included in our legal hold exports to maintain a complete audit trail.
Has anyone encountered similar issues with bot conversation recordings in bulk exports? Is there a specific parameter or filter we should adjust in the bulk export job request body to ensure bot-handled voice conversations are captured correctly?
Any insights or workarounds would be greatly appreciated.
The issue likely stems from how Genesys Cloud classifies bot interactions within the recording service versus the conversation API. When a voice call is handled entirely by an AI bot (e.g., IVR or Digital Assistant with voice capabilities), it may not generate a standard voice recording entity if no human agent ever touches the session. The Recording API v2 often filters out these “bot-only” segments unless you explicitly include them via specific query parameters or by targeting the underlying media streams directly.
Instead of relying solely on conversationType=voice, try querying the Conversation API first to identify the conversationId for those bot-handled interactions. You can then use the Media API to retrieve the associated media stream IDs, which are often more reliable for bot-generated audio than the standard recording endpoints.
Here is a sample approach using the Conversation API to filter for bot-only calls:
GET /api/v2/conversations/voice?status=completed&query=botOnly:true
Once you have the conversationId, check if a recording exists by calling:
GET /api/v2/recordings/conversations/{conversationId}
If the response is empty, it confirms the recording wasn’t generated by the standard flow. In that case, you may need to enable “Record bot interactions” in your Organization Settings under Recordings. This setting ensures that even if no agent joins, the media stream is captured and available for export.
Additionally, verify that your bulk export job is not inadvertently filtering out short-duration calls, as bot interactions can sometimes be extremely brief. Adjust your durationMin parameter if necessary.
Cross-referencing the Genesys Cloud documentation on Bot Recording Configuration, this setting is often disabled by default to save storage, which explains the empty results. Enabling it should resolve the missing data issue for your legal discovery exports.
Hold up on that bulk export strategy! I am seeing a lot of teams trip over this exact “empty result” gotcha when trying to reconcile WFM adherence data with bot-only voice interactions.
Here is the thing: if you are trying to map these recordings back to agent schedules or adherence metrics later, relying solely on the Recording API for bot-only calls is a recipe for disaster. The Recording service often treats these as orphaned media streams because there is no associated agent ID in the conversation metadata.
When you publish your weekly schedules, you are likely expecting a 1:1 match between a scheduled shift and a recorded interaction. Bot-only calls break that chain.
Instead of fighting the Recording API filters, switch to the Conversation API v2 (/api/v2/conversations/voice). You can filter by routingType or specific mediaType flags that identify AI-driven sessions. Then, cross-reference the conversationId with the Recording API. It is an extra step, but it ensures you capture the metadata correctly for your legal hold requirements.
// Example filter for Conversation API to find bot-only interactions
{
"filters": [
{
"field": "routingType",
"op": "eq",
"value": "bot"
}
]
}
I ran into this last quarter when our compliance team asked for a full audit of IVR drops. The Recording API returned nothing, but the Conversation API had every single session logged. It was a nightmare to reconcile until we switched our export logic.
Also, be careful with timezone conversions. If your bots are running in a different region than your WFM schedule (like London vs Chicago), ensure you are using UTC for all timestamp comparisons. I have seen off-by-one-day errors in adherence reports because of this.
Double-check your startTime and endTime filters in the Conversation API request to match your schedule publish window exactly. It will save you hours of manual data scrubbing.