Verified API Access for AI Model Providers: A Risk-Tiered Architecture

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Implementing identity verification in front of an AI API poses a significant architecture challenge, focusing on determining when and for whom verification is necessary, rather than the verification process itself. The guide suggests a risk-based approach to verification, with access transitions such as quota increases or new key issuance being the appropriate triggers, rather than at the initial signup. A tiered system of access levels is recommended, comprising four main levels: anonymous/free, paid self-serve, high-quota/high-credit, and organization/research, each with different verification requirements and costs. Verification costs are tier-dependent, with more expensive checks reserved for higher-risk accounts, while reusable KYC and targeted verification help minimize friction for legitimate users. The guide emphasizes that identity verification serves as a response to behavioral alerts rather than a standalone detection mechanism, advocating for a workflow-based approach that allows for policy adjustments without code changes.

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