Building an AI prototype is usually straightforward.
You pick a model, write a request, test the response, and adjust the prompt.
But moving from prototype to production changes the problem.
You start caring about:
- Which models are available
- How usage is tracked
- Where integration docs live
- How API access is managed
- How dashboards are organized
- How teams understand the workflow
The API layer becomes more than just a request and response. It becomes part of the product infrastructure.
That is the kind of problem ChinaRouter is focused on.
ChinaRouter is a unified AI API gateway and admin dashboard. It is designed to help developers and teams organize model access, usage lookup, documentation, and dashboard workflows.
Website: https://chinarouter.net/
If you have moved an AI prototype into production, what part of API management became painful first?
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