A multitude of data can be pulled from a vehicle analysis. Automakers hold millions of reports about produced cars that often encourage future automotive developments. If automakers choose not to analyze their collected information, they sacrifice opportunities for not only revenue but also increasing the safety and satisfaction of drivers.

Data-driven companies are popping up worldwide intending to enable​ new services for the industry. If Original Equipment Manufacturers chose to fulfill these tasks themselves, they would have to come up with their own AI machines to analyze data. Therefore, the companies are looking toward outside organizations to execute the research and tools for them.

Specifically, one machine learning startup that raised $11 million. Now the company will give insight to automakers about vehicles. The company plans to use artificial intelligence by way of machine learning.  Timing is an issue; to aid clients, companies need to face leveraging asynchronous time-series data. After all, gathering and analyzing this type of data is no simple task.

One interesting approach these companies are taking is instituting an assessment of estimated component failure risk. Therefore, before mass producing and releasing vehicles, companies can gauge the likelihood of needed to issue a recall. This can save billions of dollars per year in production for automakers.  Additionally, vehicles now contain sensor updates that are sent to manufacturers. This data can now be leveraged.

After a quick analysis of ongoing reports, automakers can alter vehicles in the production process. This information allows for crucial changes to be made early on in the release of new models.  In the Auto industry, the data-driven approach has only just begun to make an impact; However, manufacturers, machine learning startups, and consumers will benefit from companies leaping toward the future of auto analysis.