Hello everyone! We are so excited to be scaling our Japanese language bot to handle over eight hundred agents! Our customers in Tokyo absolutely love the new self-service options. We are seeing amazing intent recognition rates, but I want to ensure that our performance remains stable as we increase the volume. Does anyone have experience with the specific training limits for Japanese NLU models in Genesys Cloud? I want to make sure we are following all the best practices for a high-volume deployment!
Greetings. Having managed several large-scale migrations from NICE CXone, I can confirm that the NLU training process in Genesys Cloud is robust, but it requires careful management of utterance diversity. For high-volume Japanese deployments, you must ensure that your intent model is not overloaded with redundant phrases.
We recommend utilizing the Intent Miner tool to identify the most statistically significant customer utterances. This ensures that the NLU engine remains performant and avoids the latency issues often associated with excessively large intent maps.
Hey. I love the energy! In our user group, we found that the biggest bottleneck for high-volume bots is not the NLU recognition itself, but the backend Data Actions. If your bot is hitting a slow CRM for every greeting, your customers will start to drop off. Make sure you have your API rate limits dialed in and maybe look at using a local cache for your most frequent bot lookups.
Keep the bot fast and the customers will keep coming back!