Use Cases

Innovating the future in edge computing.


Regular maintenance is necessary in all industries for keeping assets in good shape, but it is time consuming and costly, and sometimes things break anyway. If you make your products talk to you, they can continuously inform you about their current condition and tell you when sensor data show unexpected behaviour, or even when maintenance or part replacement is needed. Once you get an alarm, the interaction also allows you to make specific queries to your device in order to drill down and find the real reason behind the warning, before addressing the problem. This way, you can take action to avoid failure and even let the products order necessary spare parts in advance, reducing the need for inventory. Having a dialogue with your products also opens up opportunities for additional services related to your products or to your customers’ activities, and for premium service level agreements based on an improved guaranteed performance. This is all made possible by sa.engine, directly on your device.
Use Case

Mining loaders

For example, mining loaders undergo severe wear and tear, both above ground as well as under ground. Adding complexity, mining operations often have severe limitations to connectivity.

In particular, a wheel loader that is at a standstill underground is extremely costly for operations. Not only does it block other vehicles in the mining facility, but it reduces production and the turnaround of getting a technician in place is usually long.

SA Engine allows the mining vehicles to predict when an anomaly is going to occur, and also the kind of expected failure, ensuring that they can evacuate the mine before breaking down. Furthermore, since the analysis is made locally, it can be transmitted once connectivity is established, making scarce connectivity irrelevant.

Usage & Cost

Many companies have little knowledge about how their products are used once they have been delivered. One exception is products that are always connected, but managing and analyzing continuous data streams from a large number of products in the cloud is costly and it limits what you can do in real time. Making your products send intelligent messages to you, based on models that you can change whenever you want, you will be able to get a true understanding of how your product is used at every moment.
Use Case

Autonomous vehicles

For example, vehicles with sa.engine installed can report exactly how drivers are using them in certain conditions, giving important cues for further design of the vehicle and of particular functions that would be needed and appreciated by the drivers and the passengers.

In particular, the local analysis on the product can focus on wear and tear, based on vibrations and other complex information on machine usage. Uploading a financial model of their choice directly to the product, your financial staff can let it communicate the real cost of usage at any moment, making it possible to offer your product as a service.


Product development traditionally requires lengthy phases of trial and error, slowly adjusting and improving the performance of a technology or of a certain design. Today, such methods are becoming obsolete. Product development has to be continuous and it must include AI based technology. Adjustments, corrections, and improvements have to be implemented immediately, and it has to be easy. Our tool sa.engine provides your products with the capability to make any data stream analysis you need, directly on the device, and also to communicate the result continuously. This way, you will be able to speed up development and reduce time to market. Once the product is launched, glitches and teething problems can be fixed—not with a software update after a few hours, but instantaneously. You will also be able to increase the product lifetime and create customer stickiness, adding new features and functionality over time as they are requested or developed.
Use Case

Autonomous vehicles and lawn mowers

For example, autonomous vehicles with sa.engine installed can identify when certain conditions appear and they can then send complete data streams for a specified time period which can be studied from different aspects. Based on the analysis, the vehicle’s software can be updated on the fly for improved performance, thus closing the gap between research and development.

An autonomous lawn mower can in a similar way be upgraded after a year or two with new AI-based features, e.g. making it analyze the terrain and learn from local conditions, cutting the grass more efficiently.

This way, you will not only be able to extend the lifespan of your products, but also make them appreciate rather than depreciate over time.