The Future of Products
In a data-driven world where products operate in different conditions, they must be trained in operations to automatically adapt to run at their best for where, how, and what they are being used.
Personalized
We don’t just do inference but also training at the edge to learn the normal behavior of every individual unit or installation.
Every customer is unique and so is the way they use your products. They’ve learnt from online shopping and Netflix recommendations to appreciate an ever-improving personalized experience.
Predictive
By learning the normal behavior we can predict before a critical threshold is exceeded and detect deviations that require attention.
Reactive is too late as customers expect to know before shit hits the fan. Welcome to the service transformation where things are sold as-a-service with guarantees.
Automation
This personalized and predictive approach empowers adaptive automation to ensure that every unit always runs at its best.
The only feasible approach to instant, individually smart, and bespoke products is automation. Adaptive automation that constantly learns more.
Customer Challenges
Ekkono has top-tier customers like Volvo, Atlas Copco, Danfoss, Siemens Energy, Alfa Laval and Husqvarna, and while they are in different industries they share common challenges:
Global Markets
Selling globally means that your products face different climates, conditions, load, and are even used for different applications. What’s normal for one is an anomaly for another. The only place to learn and manage this is in operations.
Products to Solutions
The complexity of products turns them into solutions. Solutions that require expert support. Support that is unfeasible to provide manually, but where your remote services team needs instant and actionable insights to act upon when an issue is escalated.
Maintenance
Customers don’t want to call when something has broken, but expect to know before it breaks. This is a shift from reactive to proactive maintenance that requires predictive and up-to-date insights. Momentaneous measurements and a sensor threshold are insufficient to assess trends and detect deviations.
Sustainability
Product OEMs have focused on design and production, leaving it to the user to figure out how to best use their products. But to meet modern sustainability requirements, every product has to always run at its best. Customers don’t just want a good deal but they also want to do good.
Solutions
The solution is that you know how every single product you have out there is doing.
Individual condition monitoring
It's like a smart watch that is telling you how your personal vital signs compare over time and if your pulse or blood pressure is abnormal relative to your current activity. With machine learning the machine can learn this from the machine data, i.e. sensors and actuators.
Predictions
Predicting a health indicator, if that is pulse or flow, voltage, or temperature, allows you to see before a critical threshold is exceeded. And by comparing the predicted value against the actual value you will instantly detect if there is a drift or an anomaly
Genuine Edge AI
Applying the intelligence at the edge also enables the use of high-resolution sensor data rather than the blunt averages that are sent to the cloud. You can also retrain the model in case of new conditions like a change of location or a replaced wear part.
