Enforce per-customer LLM policies by identifying the organization before inference, combining its applicable restrictions, and permitting only provider connections that satisfy them. A single global setting cannot express different requirements for each enterprise buyer. Another buyer may approve a different provider, while a third needs different retention. Per-customer LLM policies let you express these requirements without maintaining a separate application for every organization.
The essential design is to identify the organization before inference, calculate the constraints that apply to the request, and permit only destinations that satisfy them. This article describes an architectural pattern. Its worked example is hypothetical, rather than a claim about a customer deployment.
Put organization identity before model selection
Your server should derive the organization from authenticated application context. A browser-supplied organization identifier is not sufficient evidence of membership. Validate that relationship in your application before sending the model request. Otherwise a person could request the policy or provider credentials of another organization.
Carry a stable organization identifier, a user identifier when available, and the product plan into the inference boundary. Avoid embedding email addresses in these identifiers when an opaque identifier works. Keep authentication decisions in your application; a gateway identifier does not establish the person's right to access your business data.
Separate the organization from the environment. Production and staging can share policy design, but should use separate credentials and records. A staging key that reaches a production provider account is an operational error even when the prompt is harmless.
Define which settings can become stricter
Different settings need different combination rules. A maximum daily allowance can use the lowest applicable value. Allowed destinations need set operations. Retention needs an explicit ordering that your implementation and tests agree on. Do not merge a policy as a generic JSON object and assume that the last value is correct.
Consider this hypothetical design:
| Setting | Product baseline | Organization requirement | Effective result |
|---|---|---|---|
| Processing destinations | EU and US | EU only | EU only |
| Approved models | Model A and Model B | Model B only | Model B only |
| Stored prompt content | Up to 30 days | None | None |
| Daily user allowance | 10 example units | 3 example units | 3 example units |
The model names and allowances here are illustrative. The useful test is whether an additional policy can silently restore a destination that another policy excluded. If it can, your combination rules do not provide the boundary the buyer expects.
Alectura combines matching policies at the request boundary, with specific operations for routing lists and stricter settings for limits and retention. Read the platform's policy explanation before translating an existing policy representation into those operations.
Apply the same restrictions to fallback
Fallback must select from the effective allowed destinations. It should not be a separate emergency path with broader access. If the only approved connection fails, return a controlled failure rather than sending the prompt to an unapproved provider.
Test this with a provider stub or simulator. Make the preferred connection fail before the response begins. Then assert that every attempted connection belongs to the allowed set. Include the empty-set case: a request with no permissible destination should not reach any provider.
Treat a partially delivered answer separately. Retrying after the client has received text can produce duplicate or inconsistent results. Your retry contract needs to specify when a new attempt is allowed, who pays for it, and how the application distinguishes a failed attempt from a completed response.
Keep provider terms separate from gateway settings
A gateway's decision to keep no prompt content does not establish what a provider retains. Check the provider account, endpoint and feature you actually use. OpenAI's data controls documentation distinguishes abuse-monitoring logs, application state and eligibility for retention controls. A local retention flag cannot grant account-level eligibility.
Represent provider commitments as configuration that an owner reviews. Do not derive them from a hostname alone or copy assumptions from a different contract. A connection change can therefore require a policy review even if the model name is unchanged.
Record enough to explain a decision
For each request, preserve a request identifier, the organization, the matched policy versions, the selected connection and the outcome. Decide separately whether prompt content is needed. A request record can explain a routing refusal without storing the rejected text.
A security review should be able to answer: which policy applied at that time, which destination was permitted, and whether the request was served or refused? A dashboard that shows only today's configuration cannot answer those historical questions reliably.
Before rollout, test missing organization identifiers, conflicting policies, disabled connections, concurrent configuration changes and provider failures. Start with one representative organization in a non-production environment. Compare expected decisions with recorded decisions before expanding access.
If you want to apply this pattern at the inference boundary, use the Alectura quickstart alongside your application authorization design. Send one non-production request with your organization identifier. Check its effective policy and recorded destination against that organization’s requirements.