Best AI Infrastructure Companies

Syntiant develops a completely digital neural decision processor and artificial intelligence (AI) computing solution. It uses low-power semiconductors to move machine learning from the cloud to the edge device enabling artificial intelligence for sensor, voice, and video applications in most battery-powered products. The company was founded in 2017 and is based in Irvine, California.

Graphcore provides AI systems and services that enable organizations to build, train and deploy models in the cloud using infrastructure processing unit (IPU) hardware. Its products include cloud infrastructure processing units, data center infrastructure processing units, bow infrastructure processing units, and more. The company serves the finance, biotech, scientific research, and consumer internet sectors. It was founded in 2016 and is based in Bristol, United Kingdom.

Run:AI builds a virtualization layer for AI workloads. By abstracting workloads from the underlying infrastructure, Run:AI creates a shared pool of resources that can be provisioned on the fly, enabling full utilization of expensive GPU to compute. IT teams retain control and gain real-time visibility – including seeing and provisioning run-time, queuing, and GPU utilization – from a single web-based UI. This virtual pool of resources enables IT leaders to view, allocate, and compute resources across multiple sites.

Deci AI provides an end-to-end deep learning acceleration platform. It allows artificial intelligence (AI) developers to build, optimize, and deploy faster and more accurate models for any environment including cloud, edge, and mobile, allowing them to transform industries. The platform is powered by Deci’s AutoNAC (Automated Neural Architecture Construction) technology, an algorithmic optimization engine that squeezes maximum utilization out of any hardware without compromising on accuracy. Deci was founded in 2019 and is based in Ramat Gan, Israel.

Deeplite is an AI software company dedicated to enabling AI for everyday life. Deeplite uses AI to automatically make other AI models faster, smaller and more energy-efficient creating highly compact, high-performance deep neural networks for deployment on edge devices such as cameras, sensors, drones, phones, and vehicles.

Lambda Labs manufactures graphics processing units cloud, workstations, servers, and laptops built for deep learning. It caters its services to businesses, governments, universities, and more. Its technology, servers, and workstations are pre-configured with common machine-learning frameworks to accelerate the training and deployment of deep-learning models. The company was founded in 2012 and is based in San Francisco, California.

Latent AI is an efficient interference platform to support the tenants of adaptive artificial intelligence (AI) for a sharp edge. It offers a quantization optimizer for edge AI devices to automate the exploration of low bit-precision AI training deploying efficient neural networks for on-device intelligence and inference, enabling software developers to feasibly access, deploy and manage AI for the edge. The company was founded in 2018 and is based in Menlo Park, California.

Neural Magic develops an inference engine that data scientists can run on computers running CPUs, rather than specialized chips like GPUs or TPUs.

OctoML offers efficient and secure deployments of machine learning and deep learning models as a managed service.

OmniML is an enterprise artificial intelligence (AI) company. OmniML enables and amplifies powerful machine learning capabilities to edge devices by bringing greater speed, accuracy, and efficiency in AI through deep learning models that bridge the gap between those devices and AI applications. Th e company was founded in 2021 and is based in San Jose, California.