We Predict Your Next Move!

Mobility, led by Automotive, is a priority vertical for Ekkono. Vehicles are constructions with components from many independent suppliers of brakes, safety, steering, driveline, batteries, seats, climate control etc, and our software can truly disrupt an entire supply chain.

Automotive, just like Industrial Components, is technically in the forefront. It is, however, more fragmented with its Lego structure of components. Every car represents multiple opportunities for Ekkono’s edge machine learning software, since the car itself has a central telematics gateway, and the components are autonomous and controlled by separate ECUs/MCUs. The component vendors can only connect through the telematics gateway, which means that they don’t have remote access to their own components. This makes machine learning on the edge the only option to develop smart self-learning features on these components.

Smart Mobility Features

  • Electrification is the E in ACES that is an acronym for the transformation the Automotive industry is going through – Autonomous, Connectivity, Electrification and Sharing.
  • Connectivity is an enabler for what we do.
  • Electrification is a catalyst for features like individual range calculation that benefits from our edge machine learning.
  • Sharing means an avatar for the driver who is currently using the car, and a separate profile for the health and status of the car. Optimal use, maintenance, and life-length become crucial when the car transfers over from the OEM’s P&L to the balance sheet through the sharing business model.

Use Cases

The use cases for Automotive are the same as for Industrial Components (from Predictive Maintenance to Auto-Tuning and Self-Installation) but also:

  • Virtual Sensors that replace expensive, redundant or hard to deploy physical sensors
  • Smart Battery Management as Automotive is going through rapid electrification

At Ekkono we don’t target Autonomous specifically, which is a crowded space for AI that focuses on deep learning and image/video processing. Instead, we see that autonomous vehicles will be the sum of many smart features, where we play a central role in enabling these features that make cars safer and more reliable already today.

More than Automotive

Besides the consumer products, i.e. cars, Automotive also has a significant and lucrative commercial segment with trucks, buses, material handling and construction equipment. Uptime, availability and added-value services are more compelling arguments here as downtime and efficiency equals money. Beyond Automotive, Mobility also hosts a wide range of vehicles like trains, ships, e-bikes and scooters that benefits from machine learning on the edge.