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title: Use and Build AI Models
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version: current
locale: en-us
portal_url: https://docs.salesforce.com/admin/current/en-us/release-notes/260-0-0/rn_data_ai_models.md
canonical_url: https://help.salesforce.com/s/articleView?id=release-notes.rn_data_ai_models.htm&release=260&type=5
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description: Create your own predictive models or connect to external AI models using Data 360.
products:
  - Cross Cloud Packages Solutions
release: "260"
---
# Use and Build AI Models

Create your own predictive models or connect to external AI models using Data 360.

- **[Explore Advanced Capabilities in the New AI Models Tab](https://help.salesforce.com/s/articleView?id=release-notes.rn_cdp_2026_spring_predictive_ai_models_update.htm&release=260&type=5)**  
    Go beyond standard predictive models and unlock advanced AI capabilities in Data 360. The Einstein Studio tab is now the AI Models tab—a simplified, centralized experience for building and managing AI models.
- **[Build Predictive Models Faster with the Enhanced Einstein Studio](https://help.salesforce.com/s/articleView?id=release-notes.rn_cdp_2026_spring_predictive_model_enhanced_model_creation.htm&release=260&type=5)**  
    Save time and identify the appropriate predictive model for your use case with the enhanced Einstein Studio workflow. By choosing your model type—binary, regression, or multiclass (Beta)—before you select data, this improvement accelerates model creation.
- **[Explore Predictive Model Lineage from Your Model Details](https://help.salesforce.com/s/articleView?id=release-notes.rn_cdp_2026_spring_predictive_model_lineage_list_view.htm&release=260&type=5)**  
    Easily track a model's lifecycle and get a traceable history of your predictive model-from training to deployment and downstream usage in Data 360. Einstein Studio now offers enhanced governance and observability that enables you to view a model's lineage directly from the model details. Get improved model auditing, transparency, and trust. Model lineage also streamlines troubleshooting and impact assessment when you retain a model in a production environment.