Zero-Log AI Inference: What It Actually Means and How to Verify It

Prompt-retention claims need scope. This post explains how to distinguish a gateway-level control from an end-to-end commitment, and how to verify the processor path instead of taking marketing at its word.

The scope of a retention claim

A provider may make a promise about its gateway while relying on upstream processors with separate terms. Ask which part of the request path is covered, how the control is implemented, and what evidence supports it.

• Gateway-level prompt retention — a statement about what the gateway persists.
• End-to-end retention — a statement that must be supported by every processor in the request path.

Neither label substitutes for current documentation and verification.

What to examine in an inference path

To assess a retention claim, examine where the request is handled and what each component records:

• Whether the gateway persists prompt or response bodies.
• What request metadata and observability data are retained.
• What the upstream processors retain, and whether their terms cover training.

Those details reveal the scope of a claim more clearly than a label does.

How to verify a provider's claim

• Ask about the persistence layer — which components store prompts, responses, or metadata?
• Ask what is logged for abuse monitoring — distinguish request metadata from request bodies.
• Check for a no-training commitment — logging and training are separate. You need both to be off.
• Look at the retention statement — identify which processor and which data type the statement covers.

The bottom line

When routing sensitive data through an API, require specific, current documentation for the gateway and each upstream processor.