Original Summary

I'm Robert, founder of GreenPT. We build an AI platform focused on energy efficiency, and we've just added a US inference region to our API. Around 20% of our website traffic comes from the US, our largest share from any single country. Potential users kept asking for the same thing: they wanted to use us, but needed inference to happen in the US. That changed how I thought about our roadmap. Sustainability and control over where data is processed are global needs. Having an EU endpoint alone wasn't enough for everyone. What we shipped US inference: https://api.us.greenpt.ai/v1 EU inference: https://api.eu.greenpt.ai/v1 The default https://api.greenpt.ai/v1 still uses EU inference. The base URL selects the region. Your existing API key works across both; there is no region setting in your account or request body. The data boundary matters: prompts and outputs are processed in the region you call. Account, billing, and usage data remain in the EU, including for US inference. This is available in the API now; region selection for chat will follow later. Model availability and pricing differ by region. GreenPT is a paid service; the regional docs explain availability and link to pricing. The biggest lesson for me: where people visit from is a useful signal, but their repeated requests told us what to build. If you're building with hosted AI, what else would you need alongside regional inference to make a provider usable for your project?   submitted by   /u/BaXRS1988 [link]   [comments]

  • 情报分类：技术学习与提效
  • 分类依据：内容涉及技术、AI、软件工具或工程实践
  • 信息来源：Reddit · SideProject
  • 发布时间：2026/9/25 02:37:27