AI Gateway

Every interaction with a large language model costs money. Tokens are how providers meter capacity, and they sit at the intersection of pricing, latency, and efficiency. Most teams understand this in isolation. What becomes significantly harder is tracking token usage across a growing landscape of workloads, teams, and providers. When

Running LLM applications in production without observability is operationally reckless. When costs spike, teams struggle to determine whether traffic increased or an agent entered a recursive loop. When quality drops, it is unclear whether prompts regressed, retrieval failed, or a new model version introduced subtle behavior changes. And when compliance

Cloudflare AI Gateway has established itself as a convenient entry point for teams looking to proxy and monitor LLM traffic. With free-tier access to basic analytics, caching, and rate limiting, it works well for lightweight AI applications running on Cloudflare's edge infrastructure. However, as organizations scale AI workloads

TL;DR: Claude Code is a powerful agentic coding tool, but it's locked to Anthropic's models by default. Bifrost, an open-source AI gateway by Maxim AI, lets you route Claude Code requests through any LLM provider, including OpenAI, Google Gemini, Mistral, and more, with a simple

TL;DR: Claude Code is a powerful terminal-based coding agent, but managing multiple MCP servers alongside it creates tool sprawl and security gaps. Bifrost, the open-source LLM gateway by Maxim AI, acts as an MCP gateway that centralizes tool connections, governance, and observability for Claude Code. Route all your Claude

TL;DR: Claude Code adoption is accelerating across engineering teams, but its token-based pricing can spiral without proper controls. Anthropic's built-in /cost command offers basic visibility, but enterprise teams need more: per-developer budgets, team-level attribution, multi-provider cost tracking, and automated spend enforcement. Bifrost, the open-source AI gateway by