Agentforce Models AI API in Batch Class
Summary
Integrating Salesforce’s Agentforce Models AI API within an Apex batch class allows developers to generate personalized welcome emails at scale. Using Database.Batchable and the Models API, the batch job processes Contact records, constructs tailored AI prompts, and updates records with AI-generated content. This approach addresses scalability and resilience in native AI integration without external callouts. Salesforce teams can extend this pattern for onboarding, support, or content generation use cases.
Takeaways
- Use Database.Batchable to scale AI model calls over large Contact sets.
- Leverage aiplatform.ModelsAPI for native Salesforce AI integration without external callouts.
- Implement error handling per record to prevent batch failure.
- Use Database.Stateful to maintain state across batch executions if needed.
- Construct dynamic AI prompts with String.format using Contact data.
Agentforce Models AI API is opening exciting doors for developers by integrating AI natively into Apex. A powerful pattern emerging (AI + Apex) by using Database.Batchable to orchestrate generative model calls at scale. Let’s break it down with a practical use case: generating welcome emails for new developers using Salesforce AI Models API . The approach involves implementing a Database.Batchable<SObject> class that iterates over Contact records. For each record, we construct a prompt using basic String.format , inject the Contact’s name and title, and send it to the AI platform. Key Benefits: Scalability : Apex batchable class handle large volumes via scope processing. Resilience : Errors per record are logged; one failure won’t block the rest. Native AI Integration : No external calls—Salesforce-hosted Gen AI via aiplatform.ModelsAPI . Gotchas: Be mindful of governor limits, especially around callouts. Handle empty or null AI responses gracefully. Use Database.