AI capabilities in DataMiner are part of the standard solution, i.e. any DataMiner System has those capabilities. We strongly believe that considering the trends in the industry (all-IP, transition from hardware to software, cloud services, etc.), a different approach is required to be able to efficiently manage those increasingly complex ecosystems. So soon, it will simply not be viable anymore to manage an operation without that kind of capabilities, it will be table stakes. Hence it is standard for any DataMiner System, and we are leading in this kind of technology.
Note also that this is not a separate module in DataMiner, these are capabilities that are engraved into the DNA of DataMiner, and they are leveraged wherever they can add value. We refer to this as Augmented Operation, because you essentially have the same UIs and the same types of information as always that you are looking at, but the AI capabilities are essentially used to augment / enrich the existing data.
To give you an example. In DataMiner you have the Trend Display to visualize time traces on metrics sourced from underlying managed ecosystem. This UI has been around for ever. But these days in that UI, you will see that DataMiner will automatically extend the graph with forecasted data (i.e. what is the anticipated behavior of that metric based on its past behavior) and it will do that for different time frames (short term, medium term, etc.). Furthermore, you will notice that DataMiner will also add visual queues on the time trace graphs, wherever it has detected what we are calling 'change events' (i.e. DataMiner intuitively interprets the data and automatically indicates where behavior is changing).
In a recent release we also introduced the first version of our tagging capability (i.e. a capability that enables operators to enrich a time trace by tagging certain area's - e.g. tag a variation in a time trace and label that as a "traffic congestion"). If operators use tags, then DataMiner will also use that information, and it will automatically start looking 24/7 to check if it sees anything similar, and if it does, it will automatically tag it for the user. These are all examples of capabilities that are fully integrated with existing UIs in a very intuitive manner, but which are really driven by quite sophisticated underlying data processing. And these are just some examples in the area of a time traces, there are already a variety of other capabilities in the area of fault management for example.
But again, it is not optional. It is standard for any DataMiner System. In the first place because we strongly believe that any network management and orchestration software without these capabilities will very quickly become obsolete. This is what our users will need to be able to continue to efficiently manage the operation of tomorrow. We have our in-house squads with experts working on this every single day, so with every release DataMiner is getting increasingly more intelligent. And all of that is continuously delivered to all customers with an active Maintenance & Support contract.