Solution Architecture
We are Cloud networking architects. When we first looked at solving a Wi-Fi service assurance problem back in 2010, we had no idea that we would end-up creating a data agnostic IoT aggregation framework, to solve it.
But as we tackled once challenge after the next, it became clear that the most elegant and ultimately the most solution was one that is completely abstracted from knowing anything about the data. Back then this was a breakthrough discovery, and it has defined our architecture ever since.
Today, we are seeing a similar trend play-out in the “no-code” movement, especially in the arena of machine learning. The big difference is we’re aggregating data from devices not datasets, which is quite a challenge since every Service Provider has a unique, ever-changing blend of CPE in their network.
Everything Agnostic
Although the genesis of Astral Analytics back in 2010 was Wi-Fi Service Assurance and we now have mature applications for that primary use case, there are hundreds of potential applications for Astral Analytics across your network.
You see, unlike most analytics and data aggregation frameworks, the Astral solution is completely data, device, network and topology agnostic. That means if there is any data anywhere in your network that you want to collect, measure, interpret and act upon, Astral Analytics may be the fastest way to realize your vision.
Consider these different ways Astral Analytics is being used today:
| SingTel | Reliance JIO | CommScope |
|---|---|---|
|
WiFi radio health and subscriber performance data is and used to automatically adjust radio settings, band assignment and more. Average subscriber performance has improved 30-40% overall, and Wi-Fi related support calls have been reduced by 62% |
WiFi radio health and subscriber performance data is and used to automatically adjust radio settings, band assignment and more. Average subscriber performance has improved 30-40% overall, and Wi-Fi related support calls have been reduced by 62% PLACEHOLDER |
WiFi radio health and subscriber performance data is and used to automatically adjust radio settings, band assignment and more. Average subscriber performance has improved 30-40% overall, and Wi-Fi related support calls have been reduced by 62% PLACEHOLDER |
WiFi radio health and subscriber performance data is and used to automatically adjust radio settings, band assignment and more. Average subscriber performance has improved 30-40% overall, and Wi-Fi related support calls have been reduced by 62%
WiFi radio health and subscriber performance data is and used to automatically adjust radio settings, band assignment and more. Average subscriber performance has improved 30-40% overall, and Wi-Fi related support calls have been reduced by 62%
WiFi radio health and subscriber performance data is and used to automatically adjust radio settings, band assignment and more. Average subscriber performance has improved 30-40% overall, and Wi-Fi related support calls have been reduced by 62%