Snowflake Expands Automotive-Focused AI Data Capabilities Amid Rising Demand for Data-Driven Manufacturing
You're reading Entrepreneur India, an international franchise of Entrepreneur Media.
Cloud computing company Snowflake has expanded its AI Data Cloud offerings for the manufacturing sector, with a particular focus on the automotive industry. The development follows a marked increase in the platform's adoption over the past year, including a 416 per cent rise in data application and collaboration projects.
According to the company, deployments of analytics and data science tools on its platform have grown by 185 per cent and 188 per cent, respectively, as manufacturers seek to improve insights, operational efficiency, and predictive capabilities. The push aligns with broader trends reshaping the automotive industry, including the growth of connected vehicles, autonomous systems, electrification, and digital manufacturing practices.
Snowflake says its latest updates are designed to address the increasing complexity and data volumes generated across the vehicle lifecycle—from design and production to logistics and after-sales. Citing internal figures, the company notes that around 80 per cent of major automotive OEMs already use its data infrastructure.
Several automotive companies, including Nissan, CarMax, and Cox Automotive, are using the platform for applications ranging from analytics and forecasting to connected vehicle data integration. Leaders in these companies have indicated that the platform has helped them respond more quickly to market demands and manage operational data more efficiently.
In India, Snowflake reports a growing interest among manufacturers looking to centralise data systems and apply AI tools across their operations. "Vehicles are evolving into connected systems, and manufacturers need to handle large volumes of data across multiple functions," said Vijayant Rai, Managing Director – India, Snowflake. "We are seeing increased focus on using data to improve decision-making and streamline production processes."
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