World’s Leading Automotive Alliance Launches Alliance Intelligent Cloud On Microsoft Azure

Renault-Nissan-Mitsubishi, the world’s leading automotive alliance, announced the production release of the Alliance Intelligent Cloud, a new platform that is enabling Renault, Nissan and Mitsubishi Motors to deliver connected services in vehicles sold in nearly all 200 markets served by the Alliance member companies.

Culminating joint development efforts between the Alliance and Microsoft, the auto industry’s first global and most ambitious connected vehicle program will be deployed utilizing cloud, artificial intelligence (AI) and IoT technologies provided by Microsoft Azure. Azure provides the Alliance with a global data platform to securely capture, manage and analyze vehicle data to deliver intelligent services based on the vast volume of data created by connected vehicles.

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Kal Mos, Global Vice President of Alliance Connected Vehicles at Renault-Nissan-Mitsubishi, said: “Today we are deploying a vehicle connectivity platform that will transform the digital experience for customers of Renault, Nissan and Mitsubishi. Through our collaboration with Microsoft, we are introducing the most powerful and far-reaching connected vehicle platform. Leveraging the size and scale of the Alliance, we have built an intelligent cloud platform that sets the pace for our industry.”

“Renault-Nissan-Mitsubishi is a longstanding partner and our first strategic partner for the Microsoft connected vehicle platform.” said Jean-Phillipe Courtois, EVP and President, Microsoft Global Sales, Marketing & Operations at Microsoft. “Today’s production release of the Alliance Intelligent Cloud enables a new generation of connected services powered by Microsoft Azure to come to market.”

The first vehicles produced with Alliance Intelligent Cloud technology will be the all-new Renault Clio and selected Nissan Leaf models sold in Japan and Europe. These are also the first vehicles powered by the Microsoft connected vehicle platform available to consumers at scale.