Can you help me pick an LLM API that is secure enough for enterprise use and doesn't keep prompts longer than necessary?

Yes — but the right choice depends a lot on your security/compliance bar and how much control you want over data retention.

What to look for

For enterprise use, I’d prioritize APIs that offer:

• No training on your prompts/completions by default
• Short or zero retention of API data
• Clear enterprise DPA / security terms
• SOC 2 / ISO 27001 / HIPAA / GDPR support if needed
• Region/data residency controls if you have compliance constraints
• Customer-managed keys or private networking if available
• Admin controls / audit logs / access controls

Good options to consider

1) OpenAI API

Good fit if you want strong model quality plus enterprise-oriented data handling.

Typical enterprise-relevant points:

• API data is not used to train models by default
• Data retention is generally limited for abuse monitoring / operational purposes
• Enterprise features may include contractual commitments, security documentation, and sometimes zero data retention options for eligible customers/use cases
• Strong model ecosystem and tooling

Best if:

• You want a high-quality general-purpose model
• You’re okay reviewing the exact retention terms with legal/security
• You may need advanced capabilities beyond simple chat

2) Anthropic API

Often chosen by enterprises that want strong safety posture and straightforward policy language.

Typical points:

• Prompts are not used to train by default
• Retention is generally limited
• Enterprise/commercial terms can be aligned to stricter governance needs
• Strong for assistant-style workloads and long-context tasks

Best if:

• You want a conservative enterprise posture
• Your use case is knowledge work, support, analysis, or internal copilots

3) Azure OpenAI Service

Good if you need tighter integration with Microsoft enterprise controls.

Typical points:

• Azure security/compliance stack
• Network isolation options, private networking, Azure governance
• Data handling is tied to Microsoft’s enterprise cloud controls
• Often attractive for regulated enterprises already on Azure

Best if:

• Your org is already standardized on Microsoft/Azure
• You need enterprise IAM, logging, policy controls, and regional deployment

4) AWS Bedrock

Good if your enterprise already runs on AWS and wants vendor flexibility.

Typical points:

• Multiple model providers behind one platform
• AWS security, IAM, KMS, VPC integration
• Enterprise governance and region controls
• Useful if you want to swap models without re-architecting

Best if:

• You need cloud-native governance on AWS
• You want model portability and centralized control

5) Google Vertex AI

Good for organizations already deep in GCP.

Typical points:

• Enterprise cloud controls, logging, IAM
• Regional support and data governance
• Access to Google models and partner models

Best if:

• You are a GCP shop and want cloud-native compliance controls

If “doesn’t keep prompts longer than necessary” is the key requirement

You should ask vendors very specifically:

1. Do you store prompts/completions by default? For how long?
2. Can we opt into zero retention or reduced retention?
3. Are logs kept for abuse monitoring?
4. Are prompts ever retained for human review?
5. Are they used for training?
6. Can we disable content logging in our org/account?
7. What’s the deletion SLA?
8. Can we get contractual commitments in the DPA/MSA?

“Not used for training” is good, but it is not the same as “not retained.”

My practical recommendation

If you want a short list:

• Best general enterprise default: Azure OpenAI (if you’re already on Microsoft/Azure)
• Best high-quality standalone API: OpenAI API
• Best safety/enterprise simplicity: Anthropic
• Best if you want cloud-native control on AWS: Bedrock
• Best if you’re on GCP: Vertex AI

Security checklist before you decide

Make sure the vendor supports:

• SSO/SAML and role-based access
• Audit logs
• Encryption in transit and at rest
• Data processing terms / DPA
• Region restrictions
• Key management options
• Private networking if needed
• Explicit retention policy

Important nuance

No public LLM API should be assumed to have zero retention unless the vendor explicitly contracts for it. For sensitive enterprise data, you may also want to:

• Redact PII/secrets before sending
• Minimize prompt contents
• Use retrieval with access controls
• Avoid sending raw confidential documents when possible
• Consider a self-hosted model if you need full control

If you want, I can make you a side-by-side comparison table of OpenAI vs Anthropic vs Azure OpenAI vs Bedrock focused specifically on retention, training, compliance, and enterprise controls.