This paper details the design and implementation of an enterprise LLM gateway aimed at managing AI model access within organizations. The gateway provides centralized control over model usage on Azure, including identity-aware routing, per-tenant metering, rate limiting, and policy enforcement. It addresses common challenges such as lack of visibility into usage costs and data security by offering a unified platform for authentication, metering, and logging of all model interactions. The design leverages tools like Terraform for provisioning and Google's Model Armor for guardrails, offering a practical reference for managing AI sprawl. AI
IMPACT Provides a blueprint for enterprises to manage and govern their LLM usage, addressing cost and security concerns.
RANK_REASON The cluster describes a technical paper detailing an architecture and design for an enterprise LLM gateway, rather than a product release or a new model.
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