May 25, 2022

Tel Aviv-based startup Run:AI, which makes it easy for developers and operations teams to manage and optimize their AI infrastructure, today announced it has raised a $75 million Series C funding round led by Tiger Global Management and Insight Partners. extended. In 2021, led the company’s $30 million Series B round. Previous investors TLV Partners and Ace Capital VC also participated in the round, bringing Run:AI’s total funding to $118 million.

Run: AI Atlas Platform helps users focus on virtualizing AI workloads and optimizing GPU resources both locally and in the cloud. It abstracts away all the hardware while still allowing developers to interact with pooled resources using standard tools such as Jupyter Notebooks, and IT can better understand how those resources are being used.

A new stage comes during the rapid growth of the company. The company said its annual recurring income is up 9 times from last year and the number of employees has more than tripled. Run: AI CEO Omri Geller attributed this to a number of factors, including the company’s ability to build a global partner network to accelerate growth and overall technology development within the company. “As organizations move out of the incubation phase and start scaling their AI initiatives, they are unable to keep up with the expected pace of AI innovation due to major challenges in managing their AI infrastructure,” he said.

image credit: Running: AI

He also noted that he believes Run:AI has an edge as enterprises modernize their infrastructure, and Run:AI’s cloud-based AI orchestration platform that connects to Kubernetes environments. This fits in well with the general trend. Geller said these customers are increasingly moving from experimentation to production, and this is where the need for an MLOPS platform with a focus on GPU usage optimization like Run:AI is quickly becoming apparent.

“As part of our product development, we have added unique features to help our AI manufacturing teams manage efficiently and scale easily. Intentional workloads require maximum throughput and extremely low latency. “Execution: AI coordinates task scheduling on the inference server, maximizing throughput and reducing latency, while optimizing GPU utilization to near 100%.”

The company plans to use the new funding to grow its team, but Gellar also said the company will consider strategic acquisitions to improve its overall platform. “Our approach will always be internal growth and we don’t have any specific area to acquire. However, if an opportunity arises to strategically acquire technologies that will accelerate our time in the market and help accelerate our market dominance, we will definitely seize the opportunity.”

Lon Jaffe, Managing Director of Insight Partners, said: “As businesses in every industry refocus to become learning systems powered by AI and human talent, there is a global demand for AI hardware chipsets such as GPUs.” “As recently highlighted in the Forrester Wave AI Infrastructure report, Run:AI creates exceptional value by enabling advanced virtualization and orchestration of AI chipsets, making training and assessment systems faster and more cost-effective. Due to the surge in demand since 2020, Run:AI has nearly quadrupled our customer base and we are thrilled to double our partnership with Omri and the Incredible Run:AI team as they increase their speed and scale. I

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