Issue Auto Resolution Tuning in NLU
Use the NLU Workbench homepage to support Issue Auto Resolution (IAR) tuning in NLU.
Summary usage and roles
Use the nlu_admin or admin role to access IAR Tuning in the NLU Workbench. IAR Tuning in the NLU Workbench requires at least the nlu_feedback_admin role. Note that the nlu_admin role contains the nlu_feedback_admin role. Also, the virtual_agent_admin role contains the nlu_admin role.
If you click on the IAR model name, you will be taken straight to tuning, in the product. You will not be taken to a model overview page, so this behavior differs from Virtual Agent or AI Search models in the NLU Workbench.
The IAR Tuning workflow
IAR admins begin their model tuning journey in the IAR Admin Console, and then land in the NLU Workbench to tune their ITSM model. If they haven't trained the ITSM model in the console yet, the workflow sends them to the Expert Feedback Loop documentation under the Boost your model performance section of the NLU Workbench.
How IAR models differ from NLU models
Unlike the Virtual Agent and AI Search tabs, the IAR tab doesn't use a Create new model button. The IAR-ITSM model that IAR admins use is a prebuilt model. IAR models can't be moved using update sets.
Exploring the NLU Workbench
At the top of the NLU Workbench page are three tabs that group Virtual Agent, Issue Auto Resolution, and AI Search models separately. Below those tabs are a list of models colored grey. In the Model column of the list, if you click the caret to the left of the model name, the model changes color from grey to white and opens to show the model's languages; status; usage; model type; number of enabled intents and mapped intents and the date when the model was last modified or last published.