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friendli-ai

High-throughput inference on FriendliAI — optimized serving engine for low-latency, cost-efficient LLMs.

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## Overview

FriendliAI builds inference infrastructure with a focus on serving efficiency:
their serving engine (with techniques like iteration-level scheduling and
optimized kernels) targets high throughput and low latency per dollar, offered
both as a managed inference service and as software for self-hosted deployment.
The positioning is infrastructure-grade efficiency — for teams serving LLMs at
scale where serving economics dominate the bill.

The distinctive angle is the engine itself: FriendliAI's research in efficient
serving (published work on scheduling and optimization) informs both their
cloud service and their deployable software. For organizations serving open
models at volume — whether on FriendliAI's cloud or their own GPUs with
FriendliAI's stack — the value is measured in tokens per dollar at target