Salesforce AI Documentation
Leverage secure, BYO-key AI to document complex Salesforce code, triggers, and automations.
Definition
Salesforce AI Documentation utilizes large language models (LLMs) to inspect Apex classes, Triggers, Flows, and Custom Objects, writing human-readable functional explanations, entry points, and architectural summaries.
Overview & Context
Writing documentation is one of the most tedious tasks for software engineers. While AI can write docs, sending proprietary Salesforce code to public cloud APIs violates corporate security policies. SF Analyzer solves this by keeping the entire execution path local and executing API calls directly to your configured provider.
Important Architecture Notice
SF Analyzer strictly enforces the local data boundary. Your Salesforce metadata, credentials, and source files never leave your system.
TL;DR (Too Long; Didn't Read)
Use private LLM API keys directly from your computer to analyze and write explanations for complex Apex, triggers, and Flows in your Salesforce org.
Key Advantages
- BYO-Key SecurityYour key is saved in secure local storage and called directly from the app to the LLM.
- Context-AwarePrompts are feeded with local metadata schemas and dependency structures.
- Auto-HealingAutomatically retries failed generations and maintains a clean wiki generation log.
Typical Use Case
Organizations requiring high-quality technical documentation for compliance, audit, or developer enablement, while maintaining a strict data privacy policy.
Analysis Workflow
Configure your preferred AI provider (Gemini, OpenAI, or Anthropic) in the settings panel.
Store the API key securely in your system's keychain (Keychain Access or Credential Manager).
Select the metadata components that require documentation or let the delta engine identify changed files.
Generate functional summaries, entry points, and notable hubs with 100% private direct API calls.
How It Compares
Compare the secure local-first workflow against traditional cloud-based SaaS vendors.
| Privacy Layer | Standard AI Copilots | SF Analyzer AI Engine |
|---|---|---|
| Code Privacy | Shared with third-party servers for training | Direct connection to API; code never stored by us |
| API Key Control | Managed by vendor; subject to markup charges | Your own key; pay only the raw tokens to the provider |
| Metadata Context | Limited to currently open file in IDE | Queries local inventory database for complete relations |
| Rate Limits | Often throttled by shared subscription pools | Respects your model limits with auto-regulated RPM delays |
Frequently Asked Questions
Find answers to technical and operational questions about Salesforce AI Documentation.
Q:Which AI providers are supported?
SF Analyzer supports Google Gemini (e.g., Gemini 2.5 Flash/Pro), OpenAI (e.g., GPT-4o, GPT-4o-mini), and Anthropic Claude. You configure the provider and enter your own API key in the app.
Q:How does the tool prevent hitting API rate limits?
The AI documentation engine features built-in rate-limit buffers (such as a 4-second delay for the free Gemini tier) and handles batch concurrency carefully to prevent 429 quota exhaustion errors.
Ready to assess your Salesforce Org?
Download the SF Analyzer desktop application. Connect your sandbox or production org via the CLI, and run the assessment 100% locally.