4 Top Deep Learning Startups Impacting The Automotive Sector

Our Innovation Analysts recently looked into emerging technologies and up-and-coming startups working on solutions for the Automotive sector. As there is a large number of startups working on a wide variety of solutions, we want to share our insights with you. Today, we are taking a look at 4 promising deep learning startups.

Heat Map: 4 Top Deep Learning Startups

For our 4 top picks, we used a data-driven startup scouting approach to identify the most relevant solutions globally. The Global Startup Heat Map below highlights 4 interesting examples out of 75 relevant solutions. Depending on your specific needs, your top picks might look entirely different.

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Hazen.ai – Intelligent Traffic Management System

Government authorities struggle with managing traffic on the roads. Drivers who violate traffic rules by making illegal U-turns or sudden lane changes pose a challenge to road safety. Startups are developing deep learning-based solutions that detect the sudden change in driving behaviors of the people on roads.

Hazen.ai is a startup based out of Saudi Arabia that develops smart traffic cameras. These cameras use video analysis and deep learning techniques to detect dangerous driving behaviors on the road. The analysis is done in real-time to understand the traffic and alert and fine the violators.

RoadE – Vehicle Health Monitoring

As most people use their vehicle for commute every day, it is crucial to keep track of the vehicle’s health and prevent any breakdowns. Startups are developing deep learning-based products that monitor and predict any requirement of maintenance to enable interventions before serious damage occurs.

The Indian startup RoadE develops predictive care solutions for vehicles. Their video processing utility (VPU) is based on deep learning and video analytics while its Auto Smart platform uses deep learning and machine learning to monitor vehicle health 24×7. The company can thereby predict the requirement for maintenance and eliminate downtime.

Univrses – Autonomous Vehicles

Object perception is a challenge for autonomous vehicles. Technology needs to match up with billions of years of evolution to match human capabilities of detection and anticipation. Startups are developing deep learning-based solutions that prepare autonomous vehicles to overcome this challenge.

The Swedish startup Univrses develops computer vision solutions for the urban environment. Its 3DAI City platform is based on its proprietary 3DAI Engine and places camera units on public vehicles. It derives meaningful data along the routes to improve the object perception of autonomous vehicles.

MDGo – Customer Data Management

Sensors installed inside vehicles collect data that is very valuable to automotive manufacturers and other related sectors. This data provides insights on use by the customers that are important for further product development. Deep learning-based solutions provide better actionable insights from the automotive consumer data as compared to traditional analytics.

The Israel-based startup MDGo offers a deep learning-enabled sensor solution that collects vehicle data during crashes. It analyzes crash data in real-time and sends it to hospitals and first responders. It is useful for effective treatment to minimize the risk of any life long impact due to the crash. Furthermore, it allows for a hassle-free settlement of insurance claims.

What About The Other 71 Solutions?

While we believe data is key to creating insights it can be easy to be overwhelmed by it. Our ambition is to create a comprehensive overview and provide actionable innovation intelligence for your Proof of Concept (PoC), partnership, or investment targets. The 5 deep learning startups showcased above are promising examples out of 75 we analyzed for this article. To identify the most relevant solutions based on your specific criteria and collaboration strategy, get in touch.