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==Overview==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'''.

=Configuration=Configuration==Configuring +AI Insight for UTAs==To configure your own a '''+AI Insight''' modelfor a specific UTA, follow these steps: # Navigate to '''Global Settings''' > '''+AI''' tab > '''+AI Insights'''.# Click the “New Insight Model” button (plus sign).# Under the '''Scope''' field, select “UTA”. With this configuration, the model data is based on Level 1 records of a specific status and type and will only be available to a single UTA.# Under the '''Name''' field, enter a descriptive name.# Under the '''AI Instructions''' field, tell the AI what you want it to do with the UTA data (Example: "Analyze grant applications and provide aggregation data").# Under '''Conversation Starters''', enter any common prompts a user may wish to ask the +AI Insight model (Example: "What is the total of requested funds for applications currently in the approved status?"). Separate each conversation starter with a line break. These conversation starters will be displayed on the chat interface for users to select.# Under '''Tracking Application''', select the desired UTA. If you wish to filter the kinds of records that will be used by the AI as training data, you can do so by using the Type and Status fields.# Set role permissions as desired. .# Click '''Upload Training Data''' to update the AI’s model with the desired Level 1 records.# Click '''Save'''. '''Note:''' To ensure the AI is using the most recent dataset, be sure to periodically press the Upload Training Data button to update the AI with the latest information from the selected Tracking Application.

Once the above configuration has been set up, users can access '''+AI Insight''' by navigating to the appropriate UTA and clicking the '''+AI Insights''' button in the action bar. If multiple '''+AI Insights''' have been configured for the UTA, the user can select the desired model from the dropdown to launch the chat window. ==Configuring +AI Insight for Your Instance==To configure a '''+AI Insight''' model available to your entire instance, follow these steps: # Navigate to '''Global Settings''' > '''+AI''' tab > '''+AI Insights'''.

# Under the '''TypeScope''' field, select "UTA" if you are creating a UTA model“Instance”. With this configuration, the model data is based on Level 1 records of a specific status and type and will only be available to a single UTAuploaded training data. Alternatively, you may also select "Organization" to create an organization GPT that Instance-wide +AI Insight models can later be accessed in through the global header. For '''+AI Insight''' models configured for organizations, data is based on uploaded training databy users.# Under the '''Name''' captionfield, enter a descriptive namesuch as “Organizational Policies and Procedures”.# The Under the '''Prompt SuggestionsAI Instructions''' field can be populated , tell the AI what you want it to do with sample prompts for commonly asked questions. These prompts will appear above the chat window when uploaded training data (Example: "Analyze the uploaded data and provide answers to user launches their '''+AI Insight''' modelqueries").# Under '''Tracking ApplicationConversation Starters''', select enter any common prompts a user may wish to ask the +AI Insight model (Example: "Outline the process for contesting a decision"). Separate each conversation starter with a line break. These conversation starters will be displayed on the desired UTA chat interface for users to use select.# Set role permissions as a training setdesired. In addition# Next, you may choose go to filter the kinds of records you want “Training Files” tab and upload all the relevant documents the AI will need in order to include by type or statusanswer in the desired manner. Set role permissions if neededIf uploading a PDF file, avoid using tables and make sure all the text is selectable for the best results.