When building a small AI demo, working with APIs usually feels simple.
You choose a model, send a request, test the response, and move on.
But once the project grows, the workflow becomes more complicated. The hard part is often not the model itself, but everything around it:
- Where do we compare available models?
- How do we track usage across projects?
- Where do we find integration docs?
- How do we keep API access organized?
- How do we avoid switching between too many dashboards?
This is the operational layer of AI development, and it is easy to underestimate.
That is one of the reasons we started working on ChinaRouter.
ChinaRouter is a unified AI API gateway and admin dashboard that brings model marketplace access, API gateway workflow, usage lookup, dashboard management, and integration documentation into one place.
The goal is not to build another AI chat interface, but to make the API workflow around AI products easier to manage.
Website: https://chinarouter.net/
For developers building AI products: what part of API management becomes painful first?
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