5 Top Machine Learning Startups Impacting The Automotive Industry StartUs Insights

5 Top Machine Learning Startups Impacting The Automotive Industry

We analyzed 136 Machine Learning startups in automotive. Spark, iGloble, SONICLUE, S O NAH, and Autonomous Fusion develop 5 top solutions to watch out for. Learn more in our Global Startup Heat Map!

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. This time, we are taking a look at 5 promising Machine Learning (ML) startups.

Heat Map: 5 Top Machine Learning Startups

For our 5 top picks, we used a data-driven startup scouting approach to identify the most relevant solutions globally. The Global Startup Heat Map below highlights 5 interesting examples out of 136 relevant solutions. Depending on your specific needs, your top picks might look entirely different.


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Which startups develop the other 131 solutions?


Spark – Electric Vehicle (EVs) Optimization

There is a lack of trust in the performance of EVs on the road as compared to the other fuel-based vehicles in the market. This affects consumers’ acceptance of EVs across the globe. Startups are working on machine learning-based solutions to improve the performance of the EVs by assisting in charging, battery management, and optimization.

British startup Spark develops a product based on ML that estimates the range of miles an EV can travel after a full charge. The estimation is based on data collected about various parameters such as terrain and recent driving behaviors for human-driven vehicles as well as autonomous vehicles.

iGloble – Machine Learning For Quality Control

Automotive manufacturers suffer revenue losses due to the inefficient supply chains of automotive parts during the production stage. Startups are working on ML-based solutions that assist in the reduction of scrap and rework done for defective parts that result from manufacturing equipment failures. This positively impacts the per-unit cost of the production of automotive parts.

Indian startup iGloble develops a solution called Connected Design that is based on ML and artificial intelligence (AI). Connected Design improves the existing designs of automotive parts that are used in the manufacturing process. It improves the manufacturing cycle and reduces downtime by predicting equipment failures using real-time 3D simulations.

SONICLUE – Preventive Maintenance

Irregularities in the service of vehicles result in drivers getting stranded in remote areas. Even if they find a mechanic, it is not certain that the problem will be fully fixed. Startups are working on various products based on machine learning that enables the periodic maintenance of vehicles to save costs and avoid any damages to the automotive parts.

Israeli startup SONICLUE works on a product based on machine learning and signal processing that assists automotive technicians and mechanics to diagnose malfunctions in the vehicle through sound fluctuations. A defect or malfunction in any component of the vehicle causes a variation in the sound it produces. SONICLUE detects that variation and guides the mechanic towards that particular component.

S O NAH – Intelligent Parking

The average human being spends several minutes of their day looking for a parking spot. Startups are working on ML-based solutions to reduce the time and effort it takes to find a suitable parking spot for their vehicle. These solutions predict the availability of a parking spot by analyzing data about driving behaviors at any particular time.

German startup S O NAH develops a platform based on machine learning that, with the assistance of smart sensors, provides information about the availability of parking spots. These sensors can be installed in any infrastructure as well as any image processing technology such as existing CCTVs and the like.

Autonomous Fusion – Machine Learning For Autonomous Vehicles

One of the tougher challenges that machine learning-based technology face is in the development of autonomous vehicles (AVs). Making an AV respond correctly to a variety of events is vital to secure the life of, both, the passengers and pedestrians. Many startups across the globe are working on machine learning-based solutions to enable AVs to perform with greater reliability and accuracy.

The US-based company Autonomous Fusion, formerly known as Wheego Technologies, is working on a solution integrated with deep learning techniques to better equip Advanced Driver Assistance Sytems (ADAS) and self-driving vehicles. This solution predicts the nature of an event and gives appropriate time for the system to respond effectively by using a combination of proprietary and non-proprietary machine learning techniques.

What About The Other 131 Machine Learning 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 machine learning startups showcased above are promising examples out of 136 we analyzed for this article. To identify the most relevant solutions based on your specific criteria and collaboration strategy, get in touch.

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