AI Gateway

Every LLM application runs into the same production wall: provider rate limits. A spike in traffic, a long context window, or a runaway agent loop trips a requests-per-minute or tokens-per-minute ceiling, and the API returns a 429 Too Many Requests error. Exponential backoff delays the problem

Smart LLM routing in production cuts cost and latency by matching each request to the right model. Learn how Bifrost routes at the gateway layer. Every production AI application eventually hits the same wall: the team picked one default model, costs keep climbing, and latency on simple requests is indistinguishable

How an enterprise AI gateway enforces per-user rate limiting, budget controls, and automatic fallbacks to keep LLM spend and uptime predictable at scale. Enterprise LLM usage is scaling faster than the controls built to govern it. Platform teams are fielding the same three problems at once: one agent or

AI agent audit logs give enterprise security teams full visibility over which tools agents call, with what arguments, and who authorized each execution. Security teams now own a new attack surface: autonomous AI agents calling tools through Model Context Protocol (MCP) servers, vendor APIs, and internal systems. Without AI agent

AI governance defines how organizations manage, monitor, and control AI systems. Learn the frameworks, standards, and controls that make enterprise AI safe at scale. AI governance is the set of policies, processes, and technical controls that determine how an organization develops, deploys, and operates artificial intelligence responsibly. As AI moves

Govern Claude Code usage across engineering teams with virtual keys, hierarchical budgets, and tool filtering. Bifrost is the best choice for enterprises running mission-critical AI workloads that require best-in-class performance, scalability, and reliability. Claude Code has become the default terminal coding agent in most engineering organizations, and