Can anyone explain why the POST /api/v2/architect/flows validation passes but execution fails with a 500 Internal Server Error when triggering the Genesys AI summarization data action? We are migrating from Zendesk where ticket notes were auto-generated via simple triggers, so the equivalent here seems straightforward. In our test Architect flow, we have a single action configured to call the genesys.ai.summarize data action immediately after the conversation ends. The action ID is correct, and the tenant has AI capabilities enabled. However, the flow log shows the error: Data action execution failed: upstream service unavailable. This happens consistently in the EU1 region. We are using the latest Architect version and have verified the API keys. In Zendesk, we just used a webhook to an external summarizer, which was less integrated but more reliable. Is there a specific permission or resource limit we are missing for the native AI summarization feature? The error does not provide a detailed payload, just the generic 500. We need this for our post-interaction workflow mapping. Any insights on debugging this specific data action failure would be appreciated.
TL;DR: The 500 error is likely due to a mismatch between the conversation context payload and the AI summarization action’s expected input schema, specifically regarding how conversation segments are passed.
If I remember correctly, this issue often arises when migrating from simpler trigger-based systems like Zendesk to Genesys Cloud’s event-driven Architect flows. The genesys.ai.summarize action requires a specific structure for the conversation text it processes. It does not automatically ingest the entire conversation history unless explicitly configured to do so within the data action settings.
When you place the action immediately after the conversation ends, the flow might be attempting to pass a null or incomplete context object because the final ‘conversation:ended’ event does not always carry the full transcript payload in the way the AI service expects.
To resolve this, you should adjust the data action configuration in Architect. Instead of using the default dynamic values, map the conversation.transcript or conversation.events explicitly to the action’s input parameters. Ensure that the ‘Text’ field in the summarization action is populated with a concatenated string of the relevant interaction segments.
Here is a sample configuration snippet for the data action in the JSON view of your flow:
{
"name": "Summarize Conversation",
"type": "data",
"settings": {
"actionName": "genesys.ai.summarize",
"input": {
"text": "{{conversation.transcript}}",
"model": "default"
}
}
}
Additionally, verify that your organization has the necessary entitlements for Genesys AI and that the service account running the flow has the ai:summarization permission. Rate limiting can also cause 500 errors if multiple conversations end simultaneously, so consider adding a small delay or error handling block to catch transient failures. This approach ensures the AI receives a clean, structured payload, preventing the internal server error during execution.
It depends, but generally… the validation passing only checks the schema structure, not the actual runtime data availability. The 500 error usually stems from the conversationContext being empty or malformed when the action triggers.
Cause:
The genesys.ai.summarize action requires a populated transcripts array. If the flow triggers before the interaction data fully settles, or if the wrong interaction type is passed, the payload is null. This is common in outbound flows where the disconnect event fires before transcript finalization.
Solution:
Add a delay block or a check for interaction.transcripts before the AI action. Ensure the interaction ID is correctly mapped to the data action input.
"inputs": {
"conversationContext": "{{interaction.transcripts}}"
}
Verify the interaction status is completed before invoking the summarize action. This prevents the server from attempting to process undefined text blocks, which triggers the internal server error.