Neil Batlivala Podcast Transcript
Neil Batlivala joins host Brian Thomas on The Digital Executive Podcast.
Brian Thomas: Welcome to Coruzant Technologies, home of the Digital Executive podcast.
Welcome to the Digital Executive. Today’s guest is Neil Batlivala. Neil Batlivala is the co-founder and CEO of Pair Team, an AI enabled medical group focused on Medicaid and the underserved communities. As a healthcare technologist and an engineer who holds a patent in remote medical data capture, Neil’s professional experience spans across primary care, medical devices, and machine learning research as a first generation immigrant growing up abroad in India and Singapore instilled a deep passion and duty for overcoming social and economic disparities, and it has driven him to revolutionize patient care and operations within the healthcare system.
Well, good afternoon, Neil. Welcome to the show.
Neil Batlivala: Great to be here. Brian, thank you so much for having me on.
Brian Thomas: Absolutely, my friend. I appreciate you jumping on and you’re hailing outta New York. I’m in Kansas City, so we’re just an hour apart. Appreciate the time we traverse the globe every single day. And again, every podcast is very special to me.
So Neil, I’m gonna jump into your first question here. Your early life in India and Singapore exposed you to a significant social and economic disparities. How did these experiences shape your passion for healthcare, innovation and influence the founding of Pair Team?
Neil Batlivala: So, um, a little about me. I’m a, I’m a first generation immigrant kid from India who thought I’d be a doctor.
And growing up there it became very apparent to me the need for a strong safety net growing up. There. You see a lot of folks, the have and the have-nots. It’s quite a stark divide. Having folks sleeping on the street is a pretty normal occurrence as you’re just kind of going through day-to-day life. And my mom was a school teacher.
And she was the one who really instilled this sense of duty into me. You know, very early on, across the street from us, across from our school was uh, something called a gie, which is the Indian word for a slum. And this is one of the new Delhi’s largest slums and. Every day. My mom would set up a reach out program.
We’d go across the street, hang out with the kids there. It started small, you know, things like, you know, basically bringing varying snacks and food and things like that. And then it started to evolve into education and then healthcare. And I just found myself kind of next to the nursing station there.
But growing up there, it really, it really painted that picture from a very early age that there are folks in situations and disadvantaged situations. Through no fault of their own. I’ll give you one clear example that really stuck with me throughout my life, which was every day we’d be going, we’d go to school in our car and my mom would bring four egg sandwiches, one for me, one for my mom, and two for these children that lived under the bridge actually on our way to work.
And it was this little boy that was a girl and one day. We get to the bridge and the little girl isn’t there and we go up to the little boy and he goes, oh, she got hit by a car yesterday and it’s so nonchalant, so matter of fact, and it just put me in this, it was a very eye-opening position of there’s no one really looking after these two kids.
And so, you know, I’ve dedicated myself to healthcare and, uh, supporting those that needed most because of those experiences.
Brian Thomas: Thank you so much and I appreciate the story. And again, it’s the start of a great story on this podcast. Every single time as somebody’s experienced something in their life that has influenced them in one way or or another.
And growing up in India and seeing a lot of that poverty and disparity, and then your mother as a mentor, gosh, that was incredible that she did that and. Reached out and showed you the way and look at you now. You’ve, you’ve all grown up and you’re, you’re doing something even bigger than that, so that’s really awesome.
Thank you so much Neil. And Neil, you’ve had a diverse career from designing medical devices to researching machine learning applications in healthcare. How have these experiences informed your leadership at Pair Team?
Neil Batlivala: I think one of the most important things it’s kind of instilled in me is a sense of determination.
I think every single problem I’ve gone into, I’ve been pretty naive as to how to solve it, and even the complexity and the depth. Of the problem that I was entering into and through these experiencing, you know, through building out machine learning applications, this was looking at, you know, using a medical device to detect pneumonia in the lungs.
And, you know, using sound waves and seeing if you could use machine learning to see if the sound waves, you know, basically fluctuated differently when going through a liquid in the lungs. Get going through water in the lungs. And I’d never done this before. I’d never, you know, had never worked on a medical device, had never worked on, worked at looking at like diagnosis at that point.
And just jumping in head first showed me that jumping in and being determined, staying up, late nights, researching, really getting into the weeds and getting into ground truth. Like you can build up your own knowledge tree on this and you don’t need anyone to tell you how to, you can just go and do it.
And I’ve kind of taken that same mentality. Brought it into Pair. What I like to tell folks at, at Pair and the team here is we’re a bottoms up company. Meaning some companies are designed from the top down. They are, you see a problem, you design a solution from the very beginning and you kind of have the big macro, the intelligent design, so to speak, from the get go and you build towards it.
Pair Team has always been a bottoms up in that you find the bigger and more impactful problem to solve. So we went through, you know, supporting providers to then actually becoming. A medical group ourselves and then to a medical group with a network of technology enabled social support services. And this was all through very iterative kind of determination.
You know, Jeff Bezos has this very famous, you know, do it step by step there and that’s what it’s really brought into Pair when I think, when I think about these past experiences, I would say if you had, if you had to give me a shirt, it would just be, you know, determined problem solver. That’s what I think my career has led me up to before leading Pair.
Brian Thomas: That’s awesome. Thank you. I like how you picked something, obviously you talked about, uh, the sound waves in, in the medical field, but being that self-starter and having studied and learned a lot on your own and then taking that, brought that initiative and determination to the Pair Team has really helped you and the team excel and of course you are certainly a problem solver.
We heard that early on in your first answer here. So Neil AI is the cornerstone of Pair Teams approach. How do you ensure that AI applications used are both effective and equitable, especially when dealing with vulnerable populations?
Neil Batlivala: . Yeah, so I would, I would start with what I feel so passionate about AI right now in healthcare, and I’ll, and I’ll just start with, none of these are solved problems.
I think Pair Team has a unique opportunity to actually build more effective and more equitable AI use cases in the healthcare system. And the reason I feel so passionate about this is because when I took a step back. And I asked myself like, what’s changing in the world with ai? This is the first time that AI was actually able to not just do back office automation, but actually be front of house, actually have conversations with patients, have conversations with our care delivery system, interact with doctor’s offices, for example, if you’ve seen these voice and text agents that are out there and that creates access.
And so when you look at. More vulnerable populations or underserved communities. Access is one of the biggest issues. You have a need in the moment if you’re experiencing homelessness and you have a health concern, that need is now. If I’m not getting that addressed right now, I. I’m going to the emergency room or I’m going to the hospital.
And in the typical system, what happens is they have that need. The primary care office has a two week wait time, and because of that, you’re stuck. You have no choice but to go to the hospital, which is bad for the system. It’s very expensive visit, and the emergency room is just a, no one likes to go there.
And so I think AI is actually one of the ways we can bring access to. The care delivery system, particularly with virtual care, you know, text, phone call soon to have video agents that can help be multilingual for these patients, right? I think there’s over 200 languages that are spoken in the US so you get the long tail end.
Of languages, anytime, any place for patient care, it’s available 24 7. Any time of day, any any time of night for that need. It is infinitely patient, right? Some individuals, especially those that are in need, that are scared. That don’t have anyone else to really turn to, which is a lot of these, you know, more underserved communities.
Unfortunately, someone might not have family to talk to. And I remember a distinct story of one of our patients who was going through a pre-op plan ’cause they were gonna get surgery and our care manager called them and had to talk to ’em about things they couldn’t, could not eat. And so this woman was going through every single item in her cupboard asking the care manager if they could eat this or not.
And you know, then you get to things like cinnamon, like sugar, like pepper, and you realize after a little bit that this is less about the conversation of what can I eat or not. It’s more about having someone there that you can talk to. ’cause you’re kind of scared. It’s a scary thing. Right, and that’s actually what I see and un and unfortunately, we can’t provide our service to every single person on Medicaid and Medicare.
In fact, the way the healthcare system works is we can only provide our service to those that are the highest need and by highest need. It’s folks that go to the hospital. Enough such that keeping them outta the hospital would cover our labor costs. That just like how the financial sustainability model works, but if we can provide our service at a fraction of the cost of a traditional care delivery organization, then you can provide this service to everybody, right?
Like think of it, instead of it being hundreds of dollars a month, you’re talking about $10 a month in this always available AI care manager. And that’s what we’re kind of building towards. I think Medicaid is actually going to see the most impact because of these fundamental access challenges. There’s just not enough doctors in the country to support everyone’s need in the moment when they need that attention there and Pair Team is positioned to to safely deploy this technology.
So there’s a whole component here of how do you actually get it into the hands of patients. We operate a medical group so we can introduce AI services. You kind of job by job in a very controlled fashion, do gated releases and look at like confidence intervals of, are we confident that when our operations team reviews what AI agents have done, do they do it correctly?
Did they do it safely? Did they do it within an equitable fashion? Was the agent culturally competent, for example, and kind of navigated a conversation depending on the background of that individual. We have an expert team that can review all of those interactions. And then we’re building up a labeling the data set here.
So this creates a data loop on how we continue to build out stronger and stronger data sets that are now tuned to dealing with a population that relies on our country’s safety net. I.
Brian Thomas: Thank you so much. I appreciate you breaking that down for us. I know you’re passionate about AI and healthcare. It brings a big promise to healthcare, and you’ve really focused on that conversational AI for that care delivery for clinicians, that communication is vital.
And of course access is one of the biggest issues for the underserved. Right. And you’re using AI to help with the care delivery. Of healthcare for everyone, and I like to call it better, faster, cheaper, smarter, right? Mm-hmm. So you’re doing a great job there. Appreciate that. And Neil, last question of the day, looking ahead, what are your aspirations for Pair Team in the next five years and how do you envision the role of technology evolving in addressing healthcare disparities?
Neil Batlivala: There’s two parts of it. Two things that one Pair wants to do, and then I think just generally happening in the world, we’d like to open source our playbooks. The goal of Pair Team is not to hold on to the workflows and technologies that we build out, but instead show people how you can leverage both technology.
And a strong operationally focused medical group to better serve our safety net and work with, over the course of five years, actually work directly with state departments, work directly with the federal government to deploy our playbook across our safety net care delivery system. And so that’s like one component where I see us in five years is really, really working to deploy this at scale and more thinking of it as we’ve shown you how.
We’ve created the factory. Now let’s show you how to create your own factory, right? The blueprint for the factory, so to speak. And I think that’s just the most effective way to impact and bring the right quality of care to the most individuals possible there. As part of that, one of the things that I see is just to proliferate.
You know, especially with these, you look at like AI coding agents and the, and the ability to actually generate software. The safety net has been quite overlooked. With respect to software, most nonprofits do not have access to high quality tooling. One, they don’t have the funding for it. And the tooling that is out there, it has very limited budgets, right, to build it out and, um, are quite siloed in what it can do.
And so I see a more unified. System being built to connect nonprofits and not just help them be a directory service, but actually help nonprofits deliver care services and become a part of the care delivery system. So I’ll, I’ll give you an example, and this is what Pair Team does day in, day out. What if a shelter organization had had software that was connected to the local hospital so that it knew when one of its clients, one of the individuals who was staying at the shelter went to the hospital?
Or went to a primary care office and maybe that shelter could be the place where someone could get their drugs shipped so they could do an easy pickup, especially for those experiencing disabilities. The same goes for food pantries, helping to, uh, if someone has high blood pressure. Or is diabetic, how that food pantry can understand that context and help give them an appropriate nutritious meal depending on their health needs.
And I think this is a way, and something that Pair Team wants to build towards is a future where you have this shared and unified technology infrastructure across our safety net care delivery system.
Brian Thomas: Thank you. I really appreciate that. Neil, you know you did highlight a couple of things that I think is important.
Obviously you want to be an open book there, your playbook, you wanna be transparent, in fact, helping local state, maybe federal governance in your playbook. But you really highlighted that gap with having a better tool set for the safety nets. ’cause that’s what overlooked a lot of the times. And I’ve worked in healthcare a long time.
I worked at a safety net as well in tech, and so I definitely see it. So leveraging AI tech and software will definitely help in these areas and I’m glad you’re putting a focus there. I really appreciate that and Neil, it’s been such a pleasure having you on today and I look forward to speaking with you real soon,
Neil Batlivala: Brian. Likewise. Thank you so much for having me.
Brian Thomas: Bye for now.
Neil Batlivala Podcast Transcript. Listen to the audio on the guest’s Podcast Page.
