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Snowflake launches auto industry-specific AI capabilities

The latest AI Manufacturing Data Cloud update adds features aimed at helping auto manufacturers deal with massive amounts of data being created by the industry's evolution.

Snowflake on Tuesday launched an updated version of its AI Data Cloud for Manufacturing with new features geared toward the automotive industry, including data sharing capabilities to speed development cycles and an architecture designed to operationalize unstructured data.

Snowflake launched the first industry-specific version of its platform in 2021 when it released its Financial Services Data Cloud.

The AI Data Cloud for Manufacturing -- initially called the Manufacturing Data Cloud -- was made generally available in April 2023 and was Snowflake's sixth and industry-specific release.

In addition to Snowflake, vendors such as Databricks and SAS provide versions of their platforms tailored to customers in specific industries.

Such platforms are useful because they remove some of the burden of combining analytics and AI platforms with the relevant data required to address specific business needs, according to David Menninger, an analyst at ISG Software Research.

"No one needs a database or an AI platform," he said. "What they really need is a business solution. Someone needs to apply the technology to the specific business problem or opportunity that an enterprise faces. If software providers don't do that, then the enterprise needs to do it themselves. It takes more effort if they have to do it themselves and then on top of that they need to maintain it."

Based in Bozeman, Mont., but with no central headquarters, Snowflake is a data cloud vendor that now also provides AI development capabilities. Databricks is Snowflake's chief rival, but competitors also include data management specialists such as MongoDB and Teradata and tech giants such as AWS, Google Cloud and Microsoft.

Targeting the auto industry

The automotive industry is evolving.

Not only is it shifting to electric vehicles but autonomous driving, connected software-defined vehicles and advanced manufacturing also are ongoing trends. Combined, they generate massive amounts of data related to vehicle development, manufacturing, supply chain management and after-sales services.

Because of the ongoing change, the automotive industry is a reasonable target for industry-specific data management and insight-generation capabilities, according to Menninger.

"The auto industry is overwhelmed with data," he said. "Cars are basically mobile computers now with digital control of many of the systems, as well as connected car and self-driving capabilities. All these streams of data present a great opportunity for auto manufacturers to improve customer experiences and to improve their own operations."

However, improving customer experience (CX) and their own manufacturing operations generally requires AI-based analyses of large amounts of data, Menninger continued.

"To the extent Snowflake can package some of those capabilities, it makes it easier for manufacturers to realize these benefits," he said.

Tim Long, Snowflake's global head of manufacturing, likewise noted that the automotive industry's ongoing evolution, which is leading to an explosion of data, made it a logical target for industry-specific capabilities.

"Of all the industries undergoing major transformations as a result of data and AI, the automotive industry is perhaps one of the most heavily influenced," he said. "The rise of software-defined vehicles, autonomous driving systems, electrification, and advanced manufacturing processes has led to unprecedented volumes of data that are reshaping industry operations."

By combining the data sharing and AI-powered capabilities of Snowflake's data cloud with targeted data and AI applications developed by Snowflake partners in one environment, Snowflake aims to provide automotive stakeholders such as original equipment managers with real-time insights.

Some of the automotive companies already using Snowflake include CarMax, Cox Automotive, Nissan and Penske Logistics, according to the vendor.

Snowflake's new automotive industry-specific capabilities are largely a combination of Snowflake's data management and AI development capabilities with a data marketplace featuring relevant data and access to tools developed by Snowflake customers and partners. Together, they are designed to enable users to do the following:

  • Develop AI and machine learning applications that enable widespread data use through natural language processing and improve efficiency through automation.
  • Use a scalable platform for connected vehicle data that features a decoupled architecture that separates storage from compute to remain efficient while managing the exponential growth of data volumes created by connected vehicles, including high-resolution sensor and camera data.
  • Share data across systems related to production and service operations -- among other aspects of the automotive development and maintenance processes -- to provide a complete view of vehicle construction, performance and CX.
  • Gain real-time visibility into the automotive supply chain to avert disruptions and control costs.
  • Share and monetize automotive data products on the Snowflake Marketplace while accessing those from other Snowflake customers.
  • Collaborate with Snowflake ecosystem partners while maintaining privacy controls and remaining compliant with ever-changing industry regulations.

Support for connected vehicle data is perhaps the highlight given that such data can be used to predict potential problems and prevent them before they arise, according to Menninger.

"This data can provide numerous benefits to vehicle owners and drivers," he said. "Predictive maintenance becomes much easier -- no more wondering when a particular service is due for the vehicle. Similarly, indications of abnormal behavior can identify when a repair is needed rather than waiting until a more serious issue arises."

Next steps

In addition to the automotive, Snowflake provides targeted capabilities to other manufacturing sub-sectors including energy, industrial manufacturing and logistics, according to Long.

Looking ahead, while Long didn't provide specific plans for what other industries and manufacturing sub-sectors Snowflake might also provide with targeted capabilities, he said Snowflake's long-term roadmap aims to help every enterprise achieve its potential through data and AI.

Looking more broadly at Snowflake, Menninger targeted agentic AI as an area where Snowflake should continue to focus. The vendor has introduced agentic AI capabilities but not yet made them generally available.

"It will be interesting to see what new agentic capabilities they announce as well as when the existing features will be generally available," Menninger said.

Eric Avidon is a senior news writer for Informa TechTarget and a journalist with more than 25 years of experience. He covers analytics and data management.

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