Bifrost AI Gateway Would Have Saved My App

I was showing ChefExtract to some friends when it started returning error 404 for specific operations linked to AI. After some embarrassment, I went home to figure out the problem: The model I used for those specific operations had been deprecated. And just like that, my app was failing. But I learned my lesson: relying entirely on one API creates a single point of failure (not rocket science). The easiest fallback mechanism would be to rely on a backup model. But these increase maintenance, and it doesn’t scale well. A better fix relies on AI gateways. What is an AI gateway? An AI gateway is a middleware layer that sits between your application and the LLM providers. Instead of your code calling OpenAI or Anthropic directly, it calls the gateway, and the gateway forwards the request. Concretely, a gateway buys you four things: One API for many providers. Write your code once, switch between GPT, Claude, Gemini, or a local model without rewriting anything. Automatic failover. If your primary provider fails or deprecates your model (as it happened to me), requests reroute to a backup. Users never see a 404. Cost control and caching. Budgets, rate limits, and cached responses for repeated queries, enforced in one place instead of scattered across your codebase. This is especially useful when relying on models from different providers. Observability. Every request is logged, timed, and priced, so “why is our AI bill so high?” becomes a query instead of an investigation. Once again, this is especially useful when dealing with multiple models from different providers. This is exactly what my app needed. Failover alone would have turned my deprecated-model incident into a non-event. Enter Bifrost There are many AI gateways, but eventually I explored one called Bifrost because it is open source and you can see how it operates under the hood. Bifrost is an open-source AI gateway built by Maxim AI and written in Go. Bifrost bridges your app to more than 20 providers: OpenAI,