This Startup Is Automating America's Biggest Hospitals

1. AEAaron Epstein0:00

   [upbeat music] Today I'm excited to welcome Keshav from Luminai, who is fresh off a Series B of $38 million from Peak XV. Keshav, thank you for joining.

2. KDKesava Kirupa Dinakaran0:14

   Well, thank you for having me.

3. AEAaron Epstein0:16

   Uh, maybe to start things off, tell us more about what Luminai does.

4. KDKesava Kirupa Dinakaran0:19

   So Luminai is the AI transformation partner for health systems. We help, uh, large hospitals across the US move a large amount of their operational workflows from people to computers.

5. AEAaron Epstein0:32

   Okay. Are there specific workflows, or can you walk us through one of those specific workflows that they're doing?

6. KDKesava Kirupa Dinakaran0:36

   Absolutely. So, um, so if you think about, uh, someone like the Cleveland Clinic, um, so the Cleveland Clinic is one of the most, uh, prestigious large academic medical centers in the country. And, um, uh, as you can imagine, you know, last year they did a little over 16 million patient encounters, um, where they treated some of the most complex and most nuanced, um, uh, care journeys that, that m- most hospitals in the world don't ever see. Um, and they also have a huge, uh, uh, research arm where they work on some of the most critical diseases that are happening. And as you'd imagine, for someone of that caliber, there are patients from all over the world who want to get care at the Cleveland Clinic. And, um, this is the unfortunate reality about healthcare in America, but, um, the way that most of those patients get referred into, uh, the Cleveland Clinic is through a fax.

7. AEAaron Epstein1:28

   Hmm.

8. KDKesava Kirupa Dinakaran1:28

   Um, and, um, if you think about what that means, uh, this is on one end a physician, uh, from outside the Cleveland Clinic, writing a piece of note about a particular really critical, uh, patient and then sending it to the Cleveland Clinic fax line. And then there exists operational teams on Cleveland Clinic, Cleveland Clinic's end, where their entire job is basically to look at these faxes, figure out is this sales spam that's coming to Cleveland, is this like, uh, a thank you note from some random provider, or is this a high critical cancer patient who needs, uh, immediate attention today?

9. AEAaron Epstein2:07

   Hmm.

10. KDKesava Kirupa Dinakaran2:08

    Um, and if you think about it, uh, that operational process is extremely manual, super heavy. What Luminai does is, for them, we're essentially almost like their frontline, uh, inbox agent.

11. AEAaron Epstein2:21

    Hmm.

12. KDKesava Kirupa Dinakaran2:22

    Um, where now every single, um, fax that comes in hits Luminai first. We've become sort of the, uh, the initial triage for all of these faxes, and then if it is a high critical patient, we immediately process them. If it's someone who's not as high critical, but still requires ca- care at the Cleveland Clinic, then we're essentially, you know, extracting all the information, matching it to the right patient and provider within the internal EHR, uh, and then routing it appropriately to the right department, there are thousands of departments within the Cleveland Clinic, and then kicking off sort of the scheduling process. And so this is one example of probably, you know, uh, dozens of workflows across the Cleveland Clinic that, uh, and other health systems across America, where there's... it's all just being done by people, process, and paper. Um, and what Luminai does is become sort of the data transformation layer for these institutions, where we're converting all of this unstructured data, like faxes, into structured data, and then we have a workflow engine on top where you can essentially build a set of verticalized agents to go solve very specialized and very important problems. Um, and through that, hopefully, you know, uh, with the 30% of spend, uh, that's on the administrative waste within healthcare, which is over a trillion dollars, uh, we can get rid of that, so patients actually can get care faster. And then also at the same time, these hospitals can actually run much more effectively.

13. AEAaron Epstein3:36

    It sounds incredibly valuable.

14. KDKesava Kirupa Dinakaran3:38

    Yeah.

15. AEAaron Epstein3:38

    Um, I, I'd love to back up to the beginning, and I feel like you have such, um, an incredible unique story, and talk about how you got to this point. Like, tell us about the early days growing up in India and, um, uh, I, I feel like, uh, it's interesting to hear what led to some of the motivations and what led you down this path that you're going down now.

16. KDKesava Kirupa Dinakaran3:57

    Yeah. So I actually was not, um, uh, very good academically, uh-

17. AEAaron Epstein4:02

    [laughs]

18. KDKesava Kirupa Dinakaran4:02

    ... when I, uh, grew up. And, and, um, as you'd imagine in, especially in, um, the Indian education system, if you're not good academically, um, uh, you're sort of part of a separate, uh, group of people. Um, and, um, and so I ended up kind of thinking about, you know, what are the other things that, that seem interesting? And for whatever reason, I ended up coming upon- across a Rubik's Cube. Um, and, um, I ended up basically getting super obsessed, uh, with solving Rubik's Cubes. Um, and, uh, I ended up spending maybe my entire childhood, basically, solving Rubik's Cubes. Uh, and-

19. AEAaron Epstein4:37

    How much time were you spending every day?

20. KDKesava Kirupa Dinakaran4:39

    You know, um, I got into it pretty competit- competitively, so I ended up break... essentially maybe seven or eight hours every day on top-

21. AEAaron Epstein4:49

    Wow

22. KDKesava Kirupa Dinakaran4:49

    ... of, like, middle and high school. So I'd wake up earlier than, three or four hours before school, I'd practice, and then after I'd come back from school, I'd practice, then do whatever final homework I could do and go back to sleep and do it and repeat for, like, seven years-

23. AEAaron Epstein5:00

    Wow

24. KDKesava Kirupa Dinakaran5:00

    ... sort of straight. And, uh, as you can imagine, there's some pretty crazy people in the Rubik's Cube community, 'cause they're all quirky nerds. Um, and it was a, it was a great, uh, great group of friends I ended up making. And funnily enough, to tell you how crazy some of these people were, like, I learned Rubik's Cubes from Andrej Karpathy, uh, on YouTube, who eventually-

25. AEAaron Epstein5:19

    [laughs]

26. KDKesava Kirupa Dinakaran5:19

    ... ended up founding OpenAI. Um, but, uh, yeah, that's what I did most of my sort of childhood. I ended up breaking a bunch of world records. I was the captain of the International Rubik's Cube Team, and, and, um, and yeah, so decided to spend most of my time sort of doing that.

27. AEAaron Epstein5:34

    That's, that's incredible. And, um, what was, like, your main motivation behind learning the Rubik's Cube and all the time that you, uh, that you put into it? What were you hoping to get out of that?

28. KDKesava Kirupa Dinakaran5:44

    I think there was, like, as a 11-year-old, um, there were sort of two... I guess if I reflect now retrospectively, like, there were two things I think that really, um, got me excited to keep solving Rubik's Cubes. I think one was, in India especially-It's a very meritocratic, um, academically meritocratic society in some ways. Um, and whatha- it's changing obviously now. But one of the main things that, that, uh, showed up was, hey, if you're not academically excellent, then you're not really given any attention to. And what was really interesting about the Rubik's cube community is, uh, the first day I walked in, I walked into this room filled with, like, you know, CEOs, and engineers, and doctors, and musicians, and all these people from every walk of life who are all exceptional outside of the Rubik's cube community. Who are all of varying ages. Like, who were... I had friends who were, like, five years old. I had friends who were, like, 65. And, uh, it felt like a level playing field, where what mattered was whether you were good [laughs] at solving Rubik's cubes. And, um, it didn't matter if you were an 11-year-old, uh, and you hadn't, like, done well academically or something. It was just like, "Can you solve Rubik's cube fast?" And when, for some reason, when I k- kicked off, I actually was not terrible at it.

29. AEAaron Epstein7:01

    Mm-hmm.

30. KDKesava Kirupa Dinakaran7:01

    And so I'd started realizing I was good at certain types of techniques within Rubik's cubes, that a bunch of the older folks, these are, like, PhDs and, like, uh, doctors, and all these people would come to me and be like, "Hey, what do you think about this particular problem within the Rubik's cube?" And ask me for advice. And I was like, "This is the first time I'm ever, like, experiencing this completely different interaction mode in growing up in the society I grew up in."

Episode duration: 32:51