Atlas

Callosum builds software infrastructure for heterogeneous AI compute, with a focus on orchestrating inference across different chips and hardware stacks. (callosum.com)

Daisytuner builds software that compiles and tunes code for different processors, and offers an enterprise inference stack to run AI models efficiently across hardware.

Gimlet Labs builds an inference cloud for agentic AI workloads, using heterogeneous hardware orchestration, a hardware-agnostic compiler, and kernel generation to make inference faster and more…

Inferact is an AI infrastructure startup founded by the creators and core maintainers of vLLM, focused on making large-model inference cheaper, faster, and easier to serve at scale.

Infinity is an early-stage AI infrastructure company that uses AI to automatically generate, test, and optimize low-level inference code so non-NVIDIA chips can run models more efficiently.

Kog is a Paris-based AI infrastructure startup building a real-time inference engine for AI agents, with low-level GPU engineering and LLM architecture optimizations aimed at making token…

Modular is an AI infrastructure company that builds compiler-driven software, including the MAX inference platform and Mojo language, to make model inference faster and more portable across…

RadixArk is an infrastructure-first AI company that builds large-scale inference and training systems, including open-source serving and reinforcement-learning tooling, for developers, startups…

RunAnywhere is a research-first on-device AI inference platform that provides SDKs and runtimes to run multimodal models locally on iOS, Android, web, and edge devices with a control plane for…

Wafer builds AI agents and an inference platform that continuously optimize GPU serving stacks for faster, more efficient model inference.

ZML builds a high-performance AI inference stack that helps run open-source models efficiently across different chips and production environments.