Razor Labs, Israel’s leading AI solutions company, today announced it has joined the NVIDIA Partner Network (NPN) as the first NVIDIA Service Delivery Partner in the Middle-East and Australia. As part of the NPN, Razor Labs will have access to resources that support the deployment of its deep learning algorithms, and the creation of more cost-effective solutions.
“All companies that are part of the exclusive NVIDIA Partner Network and Service Delivery Program are companies with leading-edge technology,” said Alfred Manhart, vice president of Partners & Pathway for EMEA at NVIDIA. “ Razor Labs has a massive deployment track record, a clear vision on how AI will drive business outcomes, and considerable experience using NVIDIA GPUs to accelerate AI environments and achieve measurable results with deep learning and advanced analytics.”
Razor Labs will continue to transform traditional industries by creating end-to-end AI solutions that autonomously increase revenue by optimizing throughput, predicting malfunctions, and ensuring safe production lines. The Razor Labs methodology unlocks hidden value from IoT, sensor, and big data investments.
Razor Labs understands the business and operations of an organization and uses AI to create tangible solutions. The company will deploy accurate and robust AI models that create enormous value for its global clients in industries such as mining and natural resources, manufacturing, healthcare, retail, and transportation.
Razor Labs’ inclusion in this highly selective program was based on the company’s thorough experience in developing and deploying deep learning models from a wide range of sensors, among other cutting-edge advances in AI.
“We are proud to join the NVIDIA Partner Network. I believe that this new milestone will allow us to progress faster in our mission to create AI transformation in traditional industry sectors,” said Raz Roditti, Razor Labs CEO. “Using Razor Labs’ unique AI unit technology, clients can boost their revenues and reduce costs. These AI units generate ROI by autonomously increasing throughput, predicting malfunctions in production lines and ensuring employees’ safety.”
