Private AI vs Cloud AI
Cloud AI is fast to deploy. Private AI keeps your data secure. Which is right for your business depends on your compliance requirements and data sensitivity.
At a Glance
What is the difference?
Fast to deploy. Pay per use.
Uses third-party APIs (OpenAI, Claude, Gemini). Your data is sent to external servers for processing.
Best for:
- Non-sensitive data
- Fast deployment needs
- Variable usage volumes
Not suitable for:
- HIPAA-covered data
- Attorney-client privilege
- Regulated industries
Complete data sovereignty.
Self-hosted AI running in your own infrastructure. Your data never leaves your control.
Best for:
- Regulated industries
- Sensitive client data
- Complete data control
- High-volume processing
- Audit trail requirements
Detailed Breakdown
Side-by-side comparison
Regulated Industries
Industries that require private AI
For these industries, cloud AI is often not an option.
Legal
Attorney-client privilege requires complete data confidentiality.
Use cases
- Contract review
- Case research
- Document analysis
Healthcare
HIPAA compliance prohibits sending PHI to cloud AI services.
Use cases
- Medical records
- Clinical notes
- Patient communications
Financial Services
SEC regulations and fiduciary duties require data sovereignty.
Use cases
- Portfolio analysis
- Risk assessment
- Client data processing
Decision Guide
Which should you choose?
- Your data is not regulated or sensitive
- You need fast deployment (days, not months)
- Your usage is variable or unpredictable
- You want to minimize upfront investment
- You handle HIPAA, SEC, or privileged data
- Compliance requires data to stay on-premise
- You need audit trails showing no third-party access
- High volume makes per-query pricing expensive
Need Help Deciding?
We build both cloud and private AI systems. Book a call and we will help you determine which approach fits your compliance needs and budget.