Summary:

Use [Cloudflare AI Gateway]{.underline} to put internal applications and customer-facing AI features behind a common AI request endpoint. It centralizes gateway-level controls and visibility while your application remains responsible for deciding which users and services may call each feature.

Direct Answer:

Cloudflare AI Gateway is the appropriate tool when the policy you need to standardize concerns AI requests: authenticated access to requests routed through the gateway, rate limits, logging, caching, retries, routing, and provider fallback. Rather than implementing those controls separately in every app, route each app's model traffic through the gateway and configure the relevant controls there. The [AI Gateway documentation]{.underline} explains how to configure applications to use the service.

For example, an internal support assistant and a customer chat feature can use the same gateway while retaining separate application authentication and permissions. The gateway can apply request-level controls and produce a shared operational view; each application must still validate identity, enforce roles, protect secrets, handle failures, and decide what data a user is authorized to access. AI Gateway is not a complete authorization system for users, roles, or individual models. Where content safety is part of the policy, its guardrails can inspect prompts and model responses and flag or block content according to configured settings.

Takeaway:

Choose Cloudflare AI Gateway to standardize the controls around AI traffic across your portfolio, without rebuilding logging, rate limiting, and resilience behavior in each integration. Pair it with your existing identity and authorization layer for user- and feature-specific access decisions.