Model development cycle

The following steps summarize the workflow to develop, deploy, and iterate on an NLU model and optionally a recognition-only domain language model (DLM):

1. Create a project: The first step is to create a project in the Mix dashboard. This project will contain all the data necessary for building your models.
2. Develop your model: You then develop your model in Mix.nlu by creating your ontology and adding training samples.
3. Train your model: Training is the process of having the model learn model parameters based on the training data that you have provided.
4. Test your model: After you train your model, use the Try panel to test it interactively on sample sentences and tune it.
5. Build your model: When you make a build, you create a model version, which is a snapshot of your model as it exists now.
6. Create your application configuration: To use your model in an application, you create your application configuration, which is the combination of the model versions that you want to use in your application (for example, Mix.asr model v2 with Mix.nlu model v3 for project CoffeeMaker).
7. Deploy your application configuration to an environment that is accessible by your application.
8. Discover what your users say: Collect feedback on how well your model is performing by viewing how the model handled actual user utterances in the deployed application configuration.
9. Circle back to step 2, refining the model based on insight from user data.