This article demonstrates how to integrate Amazon SageMaker with Salesforce Data Cloud to build AI/ML-powered Salesforce applications, using product recommendations as an example.

• SageMaker Data Wrangler connector enables secure data preparation from Salesforce Data Cloud without copying data
• Build and train recommendation models in SageMaker Studio using Salesforce customer data
• Package Data Wrangler preprocessing and trained models in inference pipelines for real-time predictions
• SageMaker project template automates endpoint creation and API Gateway exposure with JWT authentication
• Register models in Salesforce Einstein Studio to activate predictions within Salesforce applications
• Solution supports both traditional ML models and large language models
• Step-by-step setup includes OAuth configuration, IAM permissions, lifecycle rules, and data transformations

This integration enables enterprises to leverage Salesforce data with SageMaker's ML capabilities, deploying secure, scalable AI models directly into Salesforce workflows.