Can AI Be Trained on My Company's Confidential Documents?

Yes, you can have AI that knows your business without exposing your secrets. Here's how to do it safely.

Two Approaches

RAG: Best for Confidentiality

Retrieval-Augmented Generation:

• Your docs: Stored in your database
• AI retrieves: Pulls relevant docs when needed
• No training: AI doesn't permanently learn your data
• Revocable: Remove access = AI "forgets"

Fine-Tuning Approach

Model trained on your data:

• Embedded knowledge: AI has your expertise
• No retrieval: Doesn't need to search
• Risk: Data is part of model now
• Use case: When RAG insufficient

Data Handling by Platform

Self-Hosted AI

Maximum security option:

• Run on your servers: Data never leaves
• Models: LLaMA, Mistral, Qwen
• Cost: Hardware + hosting
• Trade-offs: Setup complexity, less capable than GPT-4

Hybrid Approach

Best of both worlds:

• Base model: GPT-4o for general capability
• Your data: In RAG system on your servers
• Architecture: AI calls your system for company info
• Benefit: Best model + your data stays controlled

Redaction Strategy

Before sending to any external AI:

• Identify sensitive: Names, numbers, trade secrets
• Redact: Replace with [NAME], [ACCOUNT], etc.
• Process: AI works with structure, not secrets
• Re-insert: Fill back after processing

Legal Considerations

For confidential training:

• DPA: Data processing agreement with vendor
• Japan: APPI compliance for personal data
• GDPR: If EU citizens involved
• Industry rules: HIPAA, financial, etc.

Security Checklist

1. Classify data: What's confidential?
2. Choose approach: RAG preferred for secrets
3. Select vendor: Right security level
4. Agreement: Data processing terms
5. Monitor: Audit access logs

Greene Solutions Approach

For confidential client data:

• RAG-first architecture
• Self-hosted or enterprise agreements
• No data storage by default
• Full audit capabilities