What is an AI gateway?
An AI gateway is a dedicated infrastructure layer between applications and LLM providers. It handles routing, failover, rate limiting, authentication, observability, and policy enforcement centrally so individual applications do not need to build these capabilities.
How is an AI gateway different from a regular API gateway?
An API gateway manages traffic between clients and backend services. An AI gateway manages traffic between applications and LLM providers with AI-specific capabilities: token-based rate limiting, prompt filtering, semantic caching, model-aware routing, and PII sanitization.
How do I avoid LLM vendor lock-in?
Introduce a provider-agnostic abstraction layer between applications and LLM providers. An AI gateway decouples application code from provider-specific APIs, making it possible to switch providers through a configuration change rather than a code rewrite.
When should I use direct LLM API integration instead of an AI gateway?
Direct integration is appropriate for early-stage prototypes, single-developer projects, or environments with a single LLM provider and no plans to scale. Once you have multiple consumers, providers, or production uptime requirements, an AI gateway is the more sustainable path.
How long does it take to migrate from direct integration to an AI gateway?
Timeline depends on the number of LLM consumers and integration complexity. Organizations following a phased approach typically complete migration in four to eight weeks. The gateway layer reduces per-service migration effort by 60–80%.