What is an LLM Gateway?

Large language models power modern AI applications—from chatbots and code assistants to document analysis and automated customer support. But deploying LLMs at scale introduces challenges that most teams aren't prepared for. Different providers have different APIs. Models have different capabilities and pricing. Requests need routing, caching, and monitoring. Security and compliance requirements add another layer of complexity. An LLM Gateway solves these problems by acting as a centralized orchestration layer between your applications and the AI models they use. Why LLMs Need a Gateway Building production AI applications without a gateway means dealing with: Fragmented APIs : OpenAI, Anthropic, Google, and other providers all have different request formats, authentication methods, and response structures Model Selection Complexity : Choosing the right model for each use case requires understanding trade-offs between cost, latency, and capability Resource Management : Token limits, rat