Quick question about configuring intent confidence thresholds in Genesys Cloud Virtual Agents. Coming from Zendesk, where we handled fuzzy matching with simple keyword rules, the NLU confidence metrics feel quite rigid. Using the Python SDK v4.0.2, I am trying to set a custom threshold via the Bot API, but I keep hitting a 400 Bad Request.
The error message states that confidenceThreshold is read-only during intent updates. In Zendesk, adjusting these weights was straightforward. Does Genesys Cloud enforce this at the model level instead? I need to tune the accuracy without triggering full retraining cycles.
Check your approach to modifying intent confidence. The API restriction exists because confidence thresholds are managed at the bot level, not the individual intent level. This design prevents fragmentation in routing logic.
Navigate to the Virtual Agent designer and select the specific bot instance.
Open the “Settings” tab and locate the “NLU” or “Intent” section.
Adjust the global confidenceThreshold slider or input field there. This change applies to all intents within that bot.
If you need per-intent control, consider using a “Fallback” intent with a lower threshold and routing logic.
Avoid using the SDK to patch intent objects directly; it often triggers 400 errors due to schema immutability.
As a WFM coordinator, I see this pattern when agents try to override system defaults. Standardizing settings upstream saves headaches later. Publish the changes and test with low-confidence phrases. The system will route better when thresholds align with your training data quality.