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Reference

Data controls

AIgateway runs a tiered program that builds training and fine-tuning datasets from gateway traffic. This page documents what that means for your account and how to control it. The legal terms live in Privacy Policy §3.6 and Terms §3 — this page is the practical reference.

By tier

TierDefaultControl
Free / trialTrain-eligibleSettings → Data & privacy, or the per-request header below
Paid (PAYG)Not collectedOpt in from Settings → Data & privacy — halves the platform fee on shared calls
EnterpriseNever collectedNo toggle — enforced in code, not just policy

Send x-aig-no-train: 1 on any request to exclude that single call from the program, regardless of your account-level setting. There is no opposite header — you cannot opt a single call in from a dashboard-level opt-out; the header can only turn collection off.

What gets collected

On a train-eligible call, we collect:

We strip API keys, webhook secrets, and any other authentication material before anything is stored. Base64/inline binary payloads are replaced with references to durably-stored media rather than embedded inline. Exact-cache hits are not captured (they are a duplicate of an already-captured pair); semantic-cache hits are, since they pair a new prompt with an existing response.

Feedback

POST /v1/feedback lets you rate a prior response by its request_id:

POST /v1/feedback
Content-Type: application/json
Authorization: Bearer sk-aig-...

{ "request_id": "req_abc123", "rating": "down", "comment": "wrong answer" }

Feedback feeds the preference dataset we use for RLHF-style fine-tuning — it is not tied to whether the original request was itself train-eligible.

Deletion

Turning off the toggle stops future collection immediately. A verified account deletion or data-subject request additionally purges data already collected under this program — see Privacy Policy §9.