"The fastest pipe on earth. Here's how we achieve blazing fast latency globally."
Every AI provider claims to be fast. We achieve some of the lowest latencies in the industry, globally. This post explains the architectural decisions and optimizations that make that possible.
Traditional AI APIs are simple: request comes in, routes to an inference server, response goes out. This works, but it's slow. Every hop adds latency. Every queue adds delay. Every handoff is a chance for things to go wrong.
The Infe network is designed from first principles for one goal: minimal time between request and first token. Every architectural decision serves this goal.
Speed doesn't come from one big win—it comes from eliminating a hundred small delays:
DNS → Load Balancer → API Gateway → Queue → Inference → Response
Request → Inference → Stream
The moment a model generates its first token, you receive it. No buffering, no batching, no waiting for the full response. Streaming isn't an option—it's the default.
Raw P50 latency is easy to optimize. What's hard is making P99 latency match P50. We obsess over tail latency—ensuring that your slowest requests are still fast. No spikes, no variance, no surprises.
The result is an AI API that feels instant, every time. Not sometimes. Not usually. Every time.