We have this incredible opportunity because all of the kind of confluence of factors are coming together, right? There's more data available. There are incredible AI tools available. And physicians as just general people rather than just necessarily being clinicians are so aware of the tools. They're using them in their own lives and they're starting to become aware of what AI can do. And it's opening people's minds up to change. And I think that's a huge kind of real shift that's happening just at the ground leveThere's also a danger in this moment. Because the problem is that the quality of the approaches varies significantly. And this is a nascent industry that doesn't necessarily understand how to judge good from bad yet. So many people will say like, well, there's an algorithm. Not there's a good algorithm or there's a bad algorithm. There's just an algorithm. And as of right now, that's kind of all seen the same way.

And yet over time, what will be very apparent is there'll be a very large number of algorithms, but to rank them, prioritize them, different cohorts, different groups, different successes, different outcomes. And so what Dandelion is really trying to do is create that framework to be able to assess these algorithms in their different components so that we can get the right solution in the right place. But at a fundamental level, to make sure that everyone is competing on quality.

And as a patient, that is the most exciting thing that is happening right now, is that AI is enabling a quality competition, a very transparent one that for us, as people who are using healthcare, can only be good.

Finally for healthcare after 30 or 40 or 50 years, it feels like of talking about going from fee-for-service to value-based care. Like is AI the tool that makes that transition? My belief is yes. And I think it's a very exciting moment because you have the data and the capabilities of both finding the right patients and also finding the right metrics.

The key to this whole thing is having high-quality enough data to use as your base data set for analysis. The one thing that we are so proud of is how much time, care, and attention we have spent to create a data set that we really feel proud of.

To the outside world that may be like, well, all data is the same or everything. If you've worked in healthcare data, you know the huge difference. And this is where our consortium partners, our health systems are so important. They are also helping us to create that context and understanding and the right journey. And because we are doing that, it allows us to assess algorithms and create.

A standard that we hope other people do in the future. We don't anticipate being the only company that's doing this. We just like to be the ones that are hopefully starting a trend that will benefit everyone.