--- sourceDocument: Brazil Enable AI sourceDocumentLink: https://www.servicenow.com/docs/r/intelligent-experiences Release : - brazil ft:locale : - en-US ft:publication_title : - Brazil Enable AI ft:clusterId : - platai bundleId : - platai workflow : - Platform --- # Explore Predictive Intelligence # Explore Predictive Intelligence {#ariaid-title1} Release version: Brazil Updated September 10, 2026 ![](https://www.servicenow.com/docs/portal-asset/ico-clock) 2 minutes to read Summarize ![AI sparkle icon](https://servicenow.com/docs/portal-asset/ai-sparkle-icon) Summarized using AI This content was generated using new OpenAI-powered functionality. Results are provided on an as is basis and are not guaranteed to be accurate or complete. ## Summary of Explore Predictive Intelligence ServiceNow® Predictive Intelligence integrates artificial intelligence (AI) and machine learning (ML) into ServiceNow applications to enhance work experiences by enabling predictive capabilities. It offers tools to create and train models using three frameworks: classification, clustering, and similarity. These models can then be accessed by any ServiceNow application via an API to deliver predictions and automate decision-making. Show full answer Show less Predictive Intelligence is available both for cloud-based ServiceNow customers and on-premise deployments. On-premise customers should coordinate with their account manager and refer to the Machine Learning Engine installation and configuration guide in the Now Support Self-Hosted Knowledge Base. ## Key Concepts and Terminology * **Artificial Intelligence:** Systems performing tasks requiring human-like intelligence. * **Machine Learning:** Models that improve predictions over time with more data. * **Models:** Algorithms and statistical methods that generate predictions from input data. * **Training:** The process of supplying data to models to improve their accuracy. * **Supervised Training:** Training using input-output pairs to establish predictive rules. * **Unsupervised Training:** Training with raw data to uncover patterns without predefined outputs. * **Training Frequency:** How often a model is retrained with new data to maintain accuracy. * **Word Corpus:** The vocabulary a model uses to assess textual similarity. ## Predictive Model Components A predictive model is configured through a **solution definition**, which specifies: * The dataset used for training (e.g., incidents resolved in the last six months). * The input fields used for predictions (e.g., incident short description). * The output field predicted by the model (e.g., incident category). * The frequency for retraining the model (e.g., every 30 days). The trained model is called a **solution** and includes metrics such as: * **Precision:** Percentage of correct predictions (e.g., 50% means half of predictions are accurate). * **Coverage:** Percentage of records receiving predictions. * **Classes:** Possible output values the model predicts, each with precision, coverage, and distribution metrics. * **Class Distribution:** Percentage of total records belonging to each output class. ## Model Frameworks The Brazil release supports three model frameworks: * **Classification:** Assigns input records to predefined categories. * **Similarity:** Identifies records that are alike based on input data. * **Clustering:** Groups records based on shared characteristics without predefined categories. ## ServiceNow Applications Leveraging Predictive Intelligence Predictive Intelligence powers various ServiceNow applications and features across business units and industries, offering pre-built solutions that can be customized to specific use cases. This capability enables customers to automate routine decisions, improve incident categorization, and enhance overall service management efficiency. ServiceNow® Predictive Intelligence is a platform function that provides a layer of artificial intelligence that empowers features and capabilities across ServiceNow® applications to provide better work experiences. ## Overview of Predictive Intelligence Predictive Intelligence is a powerful set of tools applying artificial intelligence and machine learning to make predictions. You can create and train models in three different frameworks: classification, clustering, and similarity. A trained solution can be invoked by any ServiceNow application through an API. To learn more about ways to use existing models, see [Using Predictive Intelligence](https://www.servicenow.com/docs/OWnYKf4bC8LOtWH2wQ13hw "Train and use Predictive Intelligence solutions to accomplish various tasks."). ## Predictive Intelligence for on-premise customers {#predictive-intelligence__section_l3s_gm3_lcc} Predictive Intelligence is also available for on-premise customers. If you're interested in deploying this product on-premise, contact your account manager. For on-premise installation and configuration instructions, see the complete instructions for [Machine Learning Engine installation and configuration for self-hosted customers \[KB0782052\]](https://support.servicenow.com/kb?id=kb_article_view&sysparm_article=KB0782052) in the Now Support Self-Hosted Knowledge Base. Note: Only on-premise accounts can access the Now Support Self-Hosted Knowledge Base. ## Terminology Artificial intelligence : Systems designed to do work that needs a level of human intelligence to accomplish. Machine learning : Ability for models to improve over time with more experience. Models : Collections of algorithms, math, and statistics that make predictions and decisions based on input-output data. Training : Adding or changing data that the model is based on to affect future predictions. Supervised Training : Providing input-out pairs so that the model can generate rules that connect the two. Unsupervised Training : Providing raw data so that the model can identify structures in the data set. Training frequency : How often models are retrained to incorporate new data into an existing model. Word corpus : Vocabulary that a model can use to look for textual similarity. ## Predictive model components {#predictive-intelligence__section_hmr_1y4_n3b} A predictive model includes these components, some of which you must provide. Solution definition : A data record you create and configure that specifies these values for training a predictive model. * The records used to train the model. For example, only train on incidents that are resolved or closed within the last six months. * The input fields that the model uses to make predictions. For example, use the incident short description to make a prediction. * The output field whose value the model predicts. For example, set the incident category based on the short description. * The frequency to retrain the model. For example, retrain the model every 30 days. {#predictive-intelligence__ul_jnl_jm1_22b} Solution : The solution is the result of a solution definition that you've trained in a ServiceNow datacenter. Predictive Intelligence uses the solution to predict a target field value given one or more input field values. All solutions specify these values. * The solution precision is the aggregate percentage of correct predictions. For example, a precision of 50 means that out of 100 predictions, half of them should have the correct value. * The solution coverage is the aggregate percentage of records that receive a prediction. For example, a coverage of 50 means half of all eligible records actually receive a prediction. * The solution classes are the output field values for which the model can make predictions. Each class is an output field value with a list of possible precision, coverage, and distribution metrics to choose from. For example, the Incident Categorization solution has a class for each category such as software, inquiry, and database. * The class distribution is the percentage of records from the entire table that have this particular output field value. For example, a distribution of 50 for the inquiry class means that half of incidents have the inquiry category. {#predictive-intelligence__ul_wct_5m1_22b} * **[Predictive Intelligence frameworks](https://www.servicenow.com/docs/MuyzF1WQ7tK2VqxgiK4uKw)** Predictive Intelligence provides three different model frameworks in the Brazil release: classification, similarity, and clustering. Each framework specializes in different types of predictions. * **[ServiceNow apps and features that use Predictive Intelligence](https://www.servicenow.com/docs/swZtyjWeMeUS7oIFXIZsSQ)** Learn about ServiceNow applications and features that leverage Predictive Intelligence. Solutions that you can adapt are available for various business units and industries.