What Is an LLM Gateway? Routing, Cost Control, and the Data Access Gap

An LLM gateway serves as an intermediary infrastructure layer between applications and various model APIs such as OpenAI and Google Gemini, managing model routing, failover, observability, latency, and AI expenditure across providers. While gateways efficiently handle networking issues, they do not address the challenge of providing models with authorized access to current customer data from CRM, ATS, and other business integrations. The core problem lies in obtaining and normalizing this data for real-time use, which is critical for AI features that require operational data from customer integrations. Solutions include building custom integrations, using unified integration layers like Merge or Unified, or leveraging real-time reads and writes from source APIs. The market for LLM gateways and unified APIs is evolving, with platforms moving towards integrating data access and model routing as cohesive solutions, though challenges such as latency and cost still complicate real-time data access. The priority for AI infrastructure should be resolving data access issues before optimizing model routing, as the former determines the utility of AI features.

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