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Interview past five years. The first is that people have become more comfortable with the cloud generally. Second is that we have come to realize we don’ t need to put all the data in the cloud, which we used to do. Furthermore, if it’ s specific data that comes from a sensor on a line for example, it’ s not going to be sensitive or even mean anything to anyone else.”
More recently, what Rachel refers to as edge capability has introduced another game changer.“ A lot of our solutions in the last nine months have been a combination of edge computing with native cloud services,” she confirmed. Edge puts the computing as close to possible to the source of data.“ Edge means that we can still collect and run predictive AI or Gen AI at a site, even if connectivity is spotty or if the site goes down. With that edge capability, it doesn’ t have to go to the cloud and the data stays on premises.”
This element turned out to be significant for the lab’ s client Kingspan.“ They told us that they only needed our cloud services, as their sites have good connectivity. So, we implemented on that basis, only for their Wi- Fi and connectivity to go down! They quickly pivoted to including the edge component, so they could collect data in the way they want, even at times of no connectivity. That was in our early days, and we’ re now seeing so much more happen at the edge, which creates a powerful combination with the cloud.”
Rachel noted that today there are really two cloud service providers in the smart factory space, now that Google has stood down its services. In her career before Storm Reply she worked with all three( Google, Microsoft and Amazon Web Services) and she revealed that when they set up Storm Reply, they decided to specialize in the IoT space with Amazon
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