I would start with my interests. So when I was in my undergraduate, I did my undergraduate in India and I started with bioinformatics s my undergraduate coursework. And then initially I found there is this gap between biology and computer sites. So this was the driving factor for me to bridge the gap between these two entities, which is biology and computer science on that led to my interest in developing both decides, and I pursued a master's in computer science. Along with that also continued to go save a PhD in my biomedical informatics, which is just exactly, uh, the area off my interest. And but this driving through my interest moved forward with the way of how we could use data to make meaningful sense, sort off medical informatics approaches and computer science methodology. So this led to a decision making process where I wanted to be, and throughout the process, off interest with my career. But

I'll just start with weekly workers. Um, typically, we work 40 to 60 years depending on when we released a product or when we actually, uh, are in a phase where Right now we're handling health data and we're in covered situation. So ours are like super stewed. I cannot account to that s o ni ha. You saw health information exchange. So every state has a health information exchange or multiple health information exchanges where all the facilities and the data to us and we make are we aggregate the data and make meaningful sense out to public health reporting and longitude, not health records and many things. So this is what we do. And as you can see, this is right And, uh, the front off code 19 and making data available to everyone. So the responsibilities is just that. Like, I explain what is the vision and, uh, the other thing, which is, uh, very interesting. As we work on democratization off data which is making the data available, Thio the right folks at the right time. This is health data that we're talking about, but the bye bye whole approach off using opens or students and everything and the whole idea off reducing the health care costs down. So that is what we work on

the pain points in a push in like this, you have to make a decision where you're not given complete data or the data points are unclear. And you have to make a decision with this given limited information, right, So that would be a very, very challenging thing to do. I mean, given all the use cases, like, for example, uh, we had to deploy a dashboard in less than a few weeks for it to be available for everyone. And we do not have any visibility on where it is going to go or how it is going to sustain all those things. So sometimes you have to follow your instincts and that ISS one off the things which is quite challenging and very subjective. It might change from person to person. I would make a decision which might not be the right thing for another person. But again, we all go with this, aligning to a national goal off, you know, democratization of data and everything. So that's one of the challenges I would say. Wear constantly met withdefinitely there are technological challenges. There are resources, challenges. There are other ways by which we could think about attention off resources challenges. So at this level, every single thing will come with its own ability to say that this is I do have a lot. This is not doable within the given boundaries, so that's that's one off the barriers, I would say.