What should I use if I need SOC 2 friendly AI infrastructure?

If you need SOC 2-friendly AI infrastructure, the main thing is to use services and architectures that let you control:

• data retention
• access controls
• audit logs
• vendor risk
• where data is processed
• whether customer data is used for model training

Best options

1. Private / enterprise AI providers Use enterprise offerings from major providers that support:

• no-training-on-your-data terms
• regional data processing
• SSO / SCIM
• audit logs
• encryption
• DPA / security documentation

Examples:

• Azure OpenAI
• AWS Bedrock
• Google Vertex AI
• OpenAI Enterprise / API with appropriate data controls
• Anthropic via enterprise/API channels

2. Self-hosted models If you need maximum control, self-hosting is often the most SOC 2-friendly:

• run open-source models in your own cloud account
• keep data inside your VPC
• manage logs, secrets, and retention yourself

Common stacks:

• vLLM
• TGI (Text Generation Inference)
• Ollama for smaller/internal use
• Hugging Face Inference Endpoints in private networking setups

3. AI infrastructure on compliant cloud platforms Deploy inference and pipelines on a cloud that already supports strong compliance programs:

• AWS
• Azure
• GCP

Then add:

• private networking
• KMS-managed encryption
• IAM least privilege
• centralized logging
• secret management
• data loss prevention

What to look for in a SOC 2-friendly AI stack

Your stack should support:

• No customer data training by default
• Data processing addendum (DPA)
• SSO/SAML + SCIM
• Role-based access control
• Audit logs
• Encryption in transit and at rest
• VPC/private endpoint support
• Configurable retention/deletion
• Admin controls for keys and access
• Clear subprocessors and security docs

Avoid

• consumer chat tools for production data
• unknown API providers without a DPA or security posture
• sending regulated or sensitive data to public endpoints without controls
• logging raw prompts/responses by default
• using tools that store embeddings, traces, or prompts indefinitely

Practical recommendation

If you want the safest default:

• Use AWS/Azure/GCP
• Run the model in your own account or via an enterprise AI service
• Keep all prompt/response data in your controlled environment
• Disable training and minimize retention
• Use a SOC 2-ready observability/logging setup

If you want, I can also give you:

1. a SOC 2-friendly AI vendor shortlist, or
2. a reference architecture for a compliant AI app.