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This article is about creating your own custom AI model using training data to best meet your needs. The purpose of a '''+AI Insight''' model can depend on the scope.A model within the scope of a UTA will appear in the specific UTA it was created for . A UTA level model can perform data analysis and reporting across multiple records within a single UTA. This will give you the ability to quickly query your dataset using natural language instead of building a list view filter or report. For example, you could ask '''+AI Insight''' a question like “Please “Can you list all the applications that are still in the ‘Draft’ status” status?” or “What are the award funding amounts for 2020, 2021, and 2023 respectively?”. Using the answers provided by '''+AI Insights''' can help you in several areas, such as aggregation, summarization, and prediction. It also provides the added benefit of using your own custom training set so the AI model can learn and to incorporate knowledge specific to your process within the system. Custom models can also be created at  A model with the organization level and scope of an entire instance will appear within your system header. Organizational Instance level '''+AI Insight''' models contain uploaded training data. Instance level '''+AI Insight''' models are ideal for uploading operational policies and procedures, governance policies and protocols, system usage guidelines and program specific guidelines. In this article, you will learn how to set up and both types of custom AI models. <u>'''Note:'''</u> You will need an OpenAI license to use AI features on SmartSimple. You must be a '''Global Administrator''' to enable this feature. Contact your custom modelaccount manager or [mailto:sales@smartsimple.com sales@smartsimple.com] for further information on billing and implementation. If you have an AI implementation with Microsoft Azure, be aware that some SmartSimple +AI features will not be available to you, such as '''+AI Insights'''.