How do I limit which users can call which AI models in my org?

To control which users can call which AI models in your org, the usual approach is to enforce role-based access control (RBAC) or policy-based access control at the org/project/API-key level.

Common ways to do it

1. Separate projects / workspaces

   • Put users or teams into different projects.
   • Grant each project access only to approved models.

2. Use scoped API keys

   • Issue different API keys for different teams or apps.
   • Restrict each key to a specific model set if your platform supports it.

3. Assign roles and permissions

   • Example:
     • Admin: can use all models
     • Standard user: can use only approved models
     • Restricted user: can use only low-cost or internal models

4. Enforce it in your application layer

   • If the AI provider doesn’t support fine-grained model permissions directly, add a proxy/service in front of the API.
   • The proxy checks the user identity and only allows requests to permitted models.

5. Audit and logging

   • Track who called which model.
   • Alert on disallowed or unexpected model usage.

Practical pattern

A simple policy might look like:

• Engineering: gpt-4.1, o4-mini
• Support: gpt-4.1-mini
• Interns: gpt-4.1-mini only
• Admins: all models

Then your backend checks:

• user identity
• team/role
• requested model
• allowed-model list

If you tell me which platform you’re using (for example, OpenAI, Azure OpenAI, Anthropic, Bedrock, etc.), I can give you the exact steps and an example policy setup.