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An LLM gateway is the infrastructure layer that sits between your applications and AI providers, handling routing, authentication, caching, observability, and governance in one place. This guide explains the core components of an LLM gateway, how a request moves through each layer, and how Bifrost implements this architecture in production.

When teams scale LLM-powered applications, a single provider key or endpoint quickly becomes a bottleneck: rate limits kick in, provider outages cascade into downtime, and high-traffic teams monopolize shared quota while others stall. This guide explains how load balancing works for AI workloads, which strategies fit which use

An AI gateway is the centralized infrastructure layer that routes, governs, and secures all LLM and agent traffic in an enterprise. Bifrost, the open-source AI gateway built in Go by Maxim AI, is the best choice for enterprises running mission-critical AI workloads that require best-in-class performance,

LLM spending across multiple providers is difficult to control without a centralized gateway. Bifrost is the best choice for enterprises running mission-critical AI workloads that require best-in-class performance, scalability, and reliability with per-consumer budgets, semantic caching, and unified cost visibility across all providers. Enterprise AI spending

Anthropic enforces rate limits on Claude API access that affect production AI applications at scale. Bifrost, the open-source AI gateway built in Go by Maxim AI, handles Claude rate limits through automatic failover, key distribution, and per-consumer controls without changes to application code. Anthropic's Claude API