How We Integrate AI Agents & RAG with Salesforce
How We Connect AI Systems to Salesforce
Our microservice connects to Salesforce via a Connected App using JWT Bearer Token flow. When Cases are opened, event triggers notify our pipeline. The engine queries an in-VPC vector store containing internal technical documentation, drafts an exact resolution citing internal knowledge articles, and updates Case Comments or initiates approval workflows for support leads.
API Boundaries, Authentication & Latency SLAs
Supported Salesforce Events & Webhooks
How We Protect Your Salesforce Data
- Digital certificate authentication with no stored passwords or refresh tokens.
- Field-level security enforcement respecting Salesforce user permission sets.
- TLS 1.3 encrypted transit and mutual TLS (mTLS) endpoint support.
How We Deploy This Integration in 5 Steps
Key Integration Questions Answered
Does this integration consume our daily Salesforce API call limits?
We minimize API consumption by utilizing Salesforce Composite Batch APIs (combining up to 25 sub-requests per call) and caching read-only metadata locally in Redis.
Can the AI update custom Salesforce objects?
Yes. Our pipeline dynamically inspects your schema and can create or mutate any standard or custom (__c) objects authorized by the Connected App.
AI Agents & Workflow Automation
Learn how we build end-to-end production architectures powered by this integration.
About Aurevion AI
Custom AI systems, private RAG architectures, and sovereign software development for growing engineering teams.
Aurevion AI engineers dependable production artificial intelligence systems, sovereign retrieval-augmented generation pipelines, autonomous agentic workflows, and modern high-concurrency software applications. We partner directly with engineering leaders across North America and Europe, deploying zero-trust private cloud architectures with complete intellectual property ownership, deterministic reliability guarantees, and transparent sprint-based technical team collaboration.