[API] What I learned while trying to connect multiple AI models through one API

Over the past few weeks, I’ve been experimenting with different AI providers OpenAI, Google, Mistral, etc. Each one has its own strengths, but integrating them together can get complicated fast.

I started exploring the idea of simplifying that process basically, one API that can connect to multiple AI models. I came across an example here: NAVY. It’s not about selling anything; I just found the concept interesting from a learning standpoint.

What stood out to me was how abstraction layers can reduce repetitive setup work, but they also make you think differently about transparency and performance.

I’m still figuring out how this approach affects model evaluation and flexibility, but it’s been an interesting technical exercise so far. Thought I’d share in case anyone else here has tried similar setups or built custom wrappers for multiple APIs.