Transcript of Arundo Edge Agent video
Cody Falcon: Industrial companies are often in rugged, hostile operating environments. Often in a disconnected state and very often in highly distributed architecture, where you have hundreds or thousands of assets that aren't always online or can't always reach a cloud solution. A common challenge in our customer base is data being stranded in these disconnected operating environments. Edge Agent was purpose-built from the ground up to run on existing infrastructure. How do you stream back that temperature sensor every 15 seconds in a secure fashion to a cloud environment, to put it in the hands of a data scientist, to where they can build, train and ultimately deploy an analytic model right next to the data pipeline and operationalize the output?
Jeff Jensen: Edge makes life easier in a couple of ways. One is, an ability to not only connect to the cloud, but it's also this ability to run analytics and send the output of that data back to the cloud. Edge Agent allows you to downsample the data. You're able to combine datasets and actually run local simple analytics to compress the data. Finally, you can run a model, which takes the data at the Edge, and essentially just gives you an output.
Cody: From that point forward, the only thing leaving the field, is really the insights of the predictions from the analytics.
Jeff: The industry, right now has been collecting data for 30 years. What we're changing is an ability to bring in AI machine learning down to the Edge, to run the analytics. It actually works in conjunction with a lot of the existing products that are there.
Cody: It's not about collecting data just to collect data. It's about the data that you need to drive a business outcome from analytics.
Jeff: I'm excited that we are offering the industry a new, lightweight, containerized product, to connect their assets to the cloud. Bringing a huge advantage in terms of data value, capture and ultimate improvement to the overall process and the way that companies operate.
